Hoy en día, los sistemas de imagen basados en cámaras CCD son ampliamente utilizados en numerosos campos, en particular, en el campo de la imagen científica debido a su alta resolución, alta eficiencia cuántica, amplia respuesta espectral, aceptable razón señal-ruido, linealidad, fidelidad geométrica, rápida respuesta, tamaño reducido y durabilidad.A pesar de esto, si se quiere utilizar una cámara CCD como instrumento de medida, se debe tener en cuenta que las cámaras CCD no son detectores perfectos, si no que presentan diversas fuentes de ruido inherentes a su funcionamiento que alteran los niveles digitales correspondientes a cada píxel, distorsionan la imagen real adquirida de forma desconocida y reducen la precisión radiométrica, la calidad de la imagen y su resolución.Dos de las relativamente recientes aplicaciones de los sistemas de imagen basados en cámaras CCD son la medida del color, consistente, básicamente, en estimar los valores triestímulo XYZ asociados a una muestra de color a partir de los niveles digitales de respuesta del sistema, y la reconstrucción espectral, consistente en estimar el espectro de reflectancia de una muestra de color a partir de los niveles digitales correspondientes de la respuesta del sistema.No obstante, para llevar a cabo medidas de color o reconstrucciones espectrales mediante este tipo de dispositivos es necesario realizar una caracterización o calibración previa de estos sistemas de imagen, con el objetivo de determinar la transformación que define la correspondencia entre las repuestas digitales del sistema y, por un lado, un espacio de color independiente del dispositivo, como el XYZ o el CIELAB, ya que las respuestas digitales del sistema, incluso las señales de salida RGB de un sistema de imagen tricromático, no se corresponden con los valores triestímulo independientes del dispositivo basados en el observador colorimétrico estándar de la CIE, o bien, por otro lado, el espacio de reflectancias espectrales, respectivamente.Los métodos de caracterización colorimétrica se pueden dividir en dos categorías generales: los métodos basados en las sensibilidades espectrales del sistema, algunos de los cuales normalmente sólo se aplican a configuraciones colorimétricas, es decir, con tres canales de adquisición, debido a su creciente complejidad al incrementar el numero de canales de adquisición, y los métodos basados en una carta de colores. Los métodos basados en las sensibilidades espectrales del sistema requieren el conocimiento de dichas sensibilidades para cada canal de adquisición, las cuales deben haberse determinado previamente mediante la caracterización espectral del sistema.En cuanto a los métodos de reconstrucción espectral, su principal objetivo es reconstruir el espectro de reflectancia, transmitancia o radiancia de una muestra de color a partir de las correspondientes respuestas digitales del sistema de imagen. Estos métodos se aplican habitualmente a configuraciones multiespectrales ya que los modelos lineales de espectros de reflectancia utilizados requieren como mínimo cuatro canales de adquisición para ser capaces de estimar espectros de reflectancia reales.Para que un sistema de imagen basado en una cámara CCD pueda ser utilizado como un instrumento de medida con elevada resolución espacial, de forma que la totalidad del área de detección del sistema sea útil para medir, es necesario corregir la no-uniformidad espacial de la respuesta del sistema. Con este propósito se utilizan básicamente dos tipos de técnicas. En primer lugar, las técnicas basadas en la escena se fundamentan en aplicar un algoritmo a la imagen original con el objetivo de obtener una mejora considerable en la calidad de la imagen a expensas de la precisión radiométrica. En segundo lugar, las técnicas de corrección de campo uniforme o de la nouniformidad espacial se basan en la calibración del sistema mediante dos imágenes: una imagen oscura y una imagen de campo uniforme, que se combinan linealmente con la imagen original. Este segundo tipo de técnicas permiten llevar a cabo medidas radiométricas precisas utilizando una cámara CCD. En la literatura se pueden encontrar diversas variantes de estas técnicas de corrección de campo uniforme o de la no-uniformidad espacial. La más general de estas variantes permite llevar a cabo la corrección de la no-uniformidad espacial de la respuesta del sistema de forma independiente de la nouniformidad de la iluminación de la escena, lo que resulta particularmente útil en varias condiciones de medida como, por ejemplo, en el caso de imágenes de objetos radiantes.La utilización de un sistema de imagen basado en una cámara CCD para medidas de color o reconstrucciones espectrales con elevada resolución espacial requiere la aplicación del segundo tipo de técnicas de corrección de la no-uniformidad espacial. En este trabajo se presentan la metodología experimental desarrollada para corregir las fuentes de ruido inherentes a un sistema de imagen basado en una cámara CCD, y la optimización de un algoritmo de corrección de la no-uniformidad espacial para obtener la mejor corrección posible de la no-uniformidad espacial.El principal objetivo de este trabajo es desarrollar un sistema de imagen multispectral para la medida del color. En este trabajo se presentan el diseño y desarrollo de un prototipo de sistema multiespectral en el rango visible del espectro y su minuciosa caracterización y análisis. Con este propósito se utiliza un sistema de imagen basado en una cámara CCD, por lo que es necesario llevar a cabo, en primer lugar, la corrección del ruido de la respuesta del sistema, concretamente la corrección de la no-uniformidad espacial, y, en segundo lugar, la caracterización o calibración del sistema mencionada anteriormente, para poder obtener los valores triestímulo XYZ y/o los espectros de reflectancia, respectivamente, a partir de las respuestas digitales del sistema. En este trabajo se utilizan dos sistemas de imagen basados en una cámara CCD: uno basado en una cámara CCD 10-bits color, y uno basado en una cámara CCD 12-bits monocromática refrigerada. De este último sistema se consideran dos configuraciones: una configuración colorimétrica con 3 canales de adquisición, y una configuración multiespectral con 7 canales de adquisición. La caracterización espectral se lleva a cabo sólo para la configuración colorimétrica de ambos sistemas con el objetivo de aplicar el método de caracterización colorimétrica basado en las sensibilidades espectrales del sistema. Por otro lado, se aplican diversos métodos de medida del color y reconstrucción espectral a las dos configuraciones del sistema basado en una cámara CCD 12-bits monocromática refrigerada y se comparan utilizando todas las combinaciones posibles de las cartas GretagMacbeth ColorChecker Color Rendition (CCCR) y GretagMacbeth ColorChecker DC (CCDC) como conjuntos de entrenamiento y prueba del sistema, con el objetivo de determinar los métodos más adecuados para cada configuración, es decir, los métodos que permiten conseguir la mejor precisión tanto en la medida del color como en la reconstrucción espectral para cada configuración. Al mismo tiempo se compara también el comportamiento de ambas configuraciones en términos de precisión de la medida del color y de la reconstrucción espectral.El hecho de que las sensibilidades espectrales de la mayoría de las cámaras CCD color (3 canales de adquisición) no verifiquen la condición de Luther, es decir, no sean transformaciones lineales de las funciones de igualación del color de la CIE, limita seriamente las aplicaciones colorimétricas de los sistemas basados en cámaras CCD color, dando lugar a valores triestímulo estimados dependientes del iluminante. Esta propiedad de las sensibilidades espectrales motiva el uso de sistemas multiespectrales ya que la única forma de asegurar una igualación del color para todos los observadores y bajo cambios en la iluminación es consiguiendo la igualación espectral. El método más directo para obtener información espectral de las muestras medidas es incrementar el muestreo por encima de los tres canales de adquisición tradicionales mediante filtros de banda estrecha, lo que se conoce como un sistema de imagen multiespectral. Los campos de aplicación de los sistemas deimagen multiespectral se ha incrementado enormemente en los últimos años, fundamentalmente debido a la posibilidad que ofrecen de estimar con precisión el espectro de reflectancia en cada píxel y, a partir de éste, los valores triestímulo XYZ, evitando del metamerismo.El sistema de imagen multiespectral diseñado y desarrollado en este trabajo doctoral para la medida del color está compuesto por un cámara CCD 12-bits monocromática refrigerada, una rueda de filtros motorizada y controlada vía software con un conjunto de filtros interferenciales de banda estrecha y un objetivo de focal variable. En coherencia con los resultados obtenidos en trabajos previos [Vilaseca et al., 2006] en la región NIR del espectro y extrapolándolos al rango visible, se utiliza un conjunto de siete filtros interferenciales de banda estrecha cubriendo por completo el rango visible del espectro, con la misma FWHM y longitudes de onda de pico equidistantes. Cada filtro constituye un canal de adquisición del sistema multiespectral, que corresponde a la configuración multiespectral del sistema de imagen antes mencionado.El primer paso antes de poder utilizar un sistema de imagen basado en una cámara CCD como instrumento de medida con elevada resolución espacial es llevar a cabo la corrección de las diferentes fuentes de ruido inherentes a su funcionamiento, y muy concretamente la corrección de la nouniformidad espacial de la respuesta del sensor. Con esta objetivo, en este trabajo se ha desarrollado una metodología experimental para la corrección de dichas fuentes de ruido, y se ha llevado a cabo la optimización de un algoritmo de corrección de la no-uniformidad espacial.A lo largo de este trabajo doctoral se han realizado también diversos análisis con el objetivo de mejorar la precisión de la medida del color y de la reconstrucción espectral utilizando sistemas de imagen basados en cámaras CCD.En primer lugar, considerando los conceptos básicos aplicados en imagen de alto rango dinámico (HDRI) para obtener una representación del contenido visual de una escena real independiente del dispositivo, se propone un balance de adaptación luminosa para incrementar el rango dinámico del sistema mediante la captura de imágenes con diferentes tiempos de exposición obteniendo así niveles digitales útiles para todos los píxeles. La aplicación de este balance de adaptación luminosa permite determinar el color en todos los píxeles de la imagen, incrementando así el rango dinámico del sistema [Pujol et al., 2006].En segundo lugar, se analiza la influencia del número de muestras del conjunto de entrenamiento en la precisión de la medida del color y la reconstrucción espectral con el objetivo de determinar si existe alguna relación entre la precisión y el tamaño del conjunto de entrenamiento. La precisión del sistema mejora incrementando el tamaño del conjunto de entrenamiento hasta alrededor de 110 muestras, y pasa a ser independientes del conjunto de entrenamiento utilizado para conjuntos de entrenamiento con un número de muestras igual o superior a 110.A continuación, se analizan la medida del color y la reconstrucción espectral llevadas a cabo utilizando las dos configuraciones del sistema, colorimétrica y multiespectral, en función de las gamas de colores medidas, es decir, conjuntos de muestras de color agrupadas en función de su tono, con el objetivo de determinar si estas configuraciones son especialmente sensibles a algunos tonos y/o a otras propiedades del color. En primer lugar se analizan las tendencias generales utilizando la carta CCDC como conjunto de entrenamiento y prueba y, en segundo lugar, se utilizan las 1269 muestras de color del Munsell Book of Color - Matte Collection, clasificadas en 10 tonos Munsell y cada uno de éstos en 4 sub-tonos, para analizar la influencia de la homogeneidad en tono del conjunto de entrenamiento.Se comprueba que la homogeneidad en tono del conjunto de entrenamiento permite mejorar de forma significativa la precisión del sistema tanto en la medida del color como en la reconstrucción espectral [de Lasarte et al., 2008 - 2]. Por otro lado, se utilizan tres combinaciones de conjuntos de entrenamiento y prueba de las muestras Munsell para variar el grado de homogeneidad en tono del conjunto de entrenamiento, obteniéndose los mejores resultados para los conjuntos de entrenamiento más homogéneos en tono.Los resultados obtenidos se analizan también en función de las características del color de las muestras medidas como son las coordenadas CIELAB, y las coordenadas Munsell de tono, 'value' y croma. No se observa ningún tipo de correlación entre la precisión del sistema y las coordenadas CIELAB, mientras que la precisión del sistema tiende a empeorar para muestras con valores de la coordenada Munsell Value V > 7 - 8.Se analiza también la influencia del iluminante mediante la comparación de los resultados obtenidos utilizando dos iluminantes: una lámpara incandescente y un simulador D65. Los mejores resultados se obtienen para la combinación configuración multiespectral del sistema y simulador D65 como iluminante.Seguidamente, la precisión de la medida del color y la reconstrucción espectral se analiza en función de los espectros de reflectancia de las muestras de color medidas para determinar si existe algún tipo de correlación entre ambos. Este estudio se lleva a cabo utilizando la configuración multiespectral del sistema y el iluminante D65, la carta CCDC y las muestras Munsell como conjuntos de entrenamiento y prueba. La precisión de la medida del color y la reconstrucción espectral se analizan en función de, por un lado, el área bajo la curva (AUC) de los espectros de reflectancia y, por otro lado, la suavidad de los espectros de reflectancia mediante su Transformada Discreta de Fourier (DFT), que se utiliza frecuentemente en análisis de espectros para determinar la suavidad de las curvas. Respecto al análisis del AUC, la precisión del sistema en la medida del color tiende a mejorar para muestras con AUC de sus espectros de reflectancia mayores, aunque no se puede establecer ninguna relación directa entre ambas. Esta tendencia no se observa en términos de la precisión de la reconstrucción espectral. Una mayor precisión en la reconstrucción espectral se asocia con frecuencia a espectros de reflectancia suaves, aunque tampoco se puede establecer ninguna correlación entre ambos. En cuanto al análisis de la DFT, la precisión en la medida del color parece ser independiente de la forma y/o la suavidad de los espectros de reflectancia, mientras que la mayor precisión en la reconstrucción espectral se asocia con frecuencia a un espectro de reflectancia suave, aunque no se puede establecer una correlación general entre ambas. Una vez completado el minucioso análisis del sistema multiespectral desarrollado y establecidas sus limitaciones en cuanto a precisión en la medida del color y la reconstrucción espectral, la siguiente etapa es determinar si algún otro número y/o combinación de filtros interferenciales disponibles comercialmente permitiría mejorar, al menos teóricamente, la precisión del sistema multiespectral. Con este propósito se lleva a cabo un estudio de simulación de un sistema multiespectral óptimo para la medida del color y la reconstrucción espectral. Este estudio se realiza considerando la respuesta espectral del la cámara CCD 12-bits refrigerada monocromática utilizada y una base de datos de filtros disponibles comercialmente seleccionados entre las bases de datos de Edmund Optics, OptoSigma y CVI. Se observa que la precisión del sistema se mejora al incrementar el número de filtros, aunque esta mejora está limitada y tiende a ser insignificante para un número de filtros superior a 8. Los filtros óptimos tienden a compensar la respuesta espectral de la cámara CCD sobre todo el rango visible pero teniendo en cuenta el inconveniente que suponen el desconocer las transmitancias reales de los filtros (las simulaciones dependen en gran medida de las transmitancias reales de los filtros, que no siempre se pueden simular fácilmente a partir de las especificaciones de los proveedores), la selección de un conjunto de filtros interferenciales con posiciones de pico equidistantes cubriendo todo el rango visible, iguales FWHM que permiten un ligero solapamiento entre ellos, y la mayor transmitancia posible, como se ha hecho en este trabajo, constituye una opción más que aceptable para obtener un sistema multiespectral útil. Finalmente, se comprueba la aplicabilidad del sistema multiespectral desarrollado utilizando, no sólo cartas de color estandarizadas, como son las CCDC, CCCR y las muestras Munsell, sino utilizando también un conjunto de 56 muestras textiles agrupadas en 28 parejas, que fueron especialmente fabricadas para comprobar la aplicabilidad de las fórmulas de diferencia de color, y el simulador D65 como iluminante. Se analizan diferentes combinaciones de conjuntos de entrenamiento y prueba. Los mejores resultados se obtienen, en promedio, utilizando conjuntos de entrenamiento homogéneos en tono y llevando a cabo una clasificación previa de las muestras textiles en tonos. Además, se comprueba la capacidad del sistema multiespectral desarrollado de detectar pequeñas diferencias, tanto en color como en el espectro de reflectancia, entre muestras reales, resultando así ser útil para aplicaciones que requieran discriminación, aunque se obtiene una escasa precisión en la determinación de las diferencias tanto de color como en las reflectancias espectrales entre los pares de muestras textiles considerados. / Nowadays, imaging systems based on CCD cameras are widely used in several fields and, particularly in the field of scientific image, due to its high resolution, high quantum efficiency, wide spectral response, acceptable signal-to-noise ratio, linearity, geometric fidelity, fast response, small size and durability.In spite of this, if a CCD camera is wanted to be used as a measuring instrument, one must bear in mind that CCD cameras are not perfect detectors, but there are various noise sources inherent to their performance that alter the digital levels corresponding to each pixel, distort the real image acquired in an unknown manner, and diminish the radiometric accuracy, the image quality and the resolution.Two of the relatively recent applications of the imaging systems based on CCD cameras are colour measurement and spectral reconstruction. Colour measurement basically consists of estimating the XYZ tristimulus values associated to a colour sample from the system's response digital levels, whereas spectral reconstruction consists of estimating the reflectance spectrum of a colour sample from its corresponding system's response digital levels.Nevertheless, performing colour measurements and/or spectral reconstructions using this kind of devices requires a previous characterization or calibration of the imaging system. On one hand, colour measurement requires to determine the transformation that defines the correspondence between system's digital responses and a colour space independent of the device, such as the XYZ or the CIELAB. This is due to the fact that system's digital responses, even the RGB output signals for a trichromatic imaging system, do not correspond with the device independent tristimulus values based on the CIE standard colorimetric observer. On the other hand, spectral reconstruction requires to determine the transformation that defines the correspondence between system's digital responses and the reflectance spectra space.Methods for colorimetric characterization can be divided in two general categories: methods based on spectral sensitivities, some of which are usually only applied to colorimetric configurations of imaging systems, i.e. with three acquisition channels, due to its growing complexity when the number of acquisition channels is increased, and methods based on a colour sample chart. Methods based on spectral sensitivities require the knowledge of the system's spectral sensitivities for each acquisition channel, which can be previously determined through the spectral characterization of the imaging system.Regarding the methods for spectral reconstruction, their main objective is to reconstruct the reflectance, transmittance or radiance spectra of a colour sample from the corresponding digital responses of the imaging system. These methods are usually applied to multispectral configurations since the linear models of reflectance spectrum used require at least four acquisition channels to be able to estimate real reflectance spectra.In order an imaging system based on a CCD camera can be used as a measuring instrument with high spatial resolution, so that the whole system's detection area is useful for measuring, it is mandatory to correct the spatial non-uniformity of the system's response. Basically two kinds of techniques are used with this purpose. Firstly, the scene-based techniques are based on applying an algorithm to the original or raw image in order to obtain a considerable improvement in image quality at the expense of radiometric accuracy. Secondly, the flat-field correction or spatial non-uniformity correction techniques are based on calibrating the detector by means of two images: a dark image and a uniform field or flat-field image, which are linearly combined with the original or raw image (image to be corrected). These second type techniques allow to use a CCD camera to perform accurate radiometric measurements. Several variants of these flat-field correction or spatial non-uniformity correction techniques can be found in literature. The most general of these variants allow the correction of the spatial non-uniformity of the system's response independently of the spatial non-uniformity of the scene illumination, which is quite useful in several measurement imaging conditions, such as in the case of images corresponding to self-radiating objects.Using an imaging system based on a CCD camera for high spatial resolution colour measurement and/or spectral reconstruction requires applying one of the second type techniques for the spatial non-uniformity correction. In this work, the experimental methodology developed to correct the inherent noise sources of an imaging system based on a CCD camera, and the optimization of a spatial non-uniformity correction algorithm to obtain the best spatial non-uniformity correction possible are presented.The main aim of this work is to develop a multispectral imaging system for colour measurement and spectral reconstruction. The design and development of a prototype of multispectral imaging system in the visible range of the spectrum and its thorough characterization and analysis is presented in this work. For this purpose, an imaging system based on a CCD camera is used. Therefore, in order to be able to perform accurate colour measurements and/or spectral reconstructions with high spatial resolution it will be necessary to carry out, firstly, the noise correction of the system's response, particularly the correction of the spatial non-uniformity, and secondly, the previously mentioned characterization or calibration of the imaging system to be able to obtain the XYZ tristimulus values and/or the reflectance spectra, respectively, from the system's digital responses.Two imaging systems based on a CCD camera are used in this work: an imaging system based on a colour 10-bits CCD camera, and an imaging system based on a monochrome 12-bits cooled CCD camera. Two configuration of this last imaging system are considered: a colorimetric configuration with 3 acquisition channels, and a multispectral configuration with 7 acquisition channels. The spectral characterization is carried out only for the colorimetric configuration of the previously mentioned two imaging systems, in order to be able to apply the method for colorimetric characterization based on the spectral sensitivities of the imaging system.Different methods for colour measurement and spectral reconstruction are applied to the two configurations of the imaging system based on a monochrome 12-bits cooled CCD camera, and compared using all possible combinations of the GretagMacbeth ColorChecker Color Rendition chart (CCCR) and the GretagMacbeth ColorChecker DC chart (CCDC) as training and test sets, in order to determine the most suitable methods for each configuration, i.e., the methods that allow to achieve the best accuracy of both colour measurement and spectral reconstruction for each configuration. At the same time, the performance of the two configurations is also compared in terms of both accuracy of colour measurement and accuracy of spectral reconstruction.The fact that the spectral sensitivities of most of the commercial colour CCD cameras (3 acquisition channels) do not verify the Luther condition, i.e., are not linear transformations of the CIE colour matching functions, seriously limitates the colorimetric applications of the imaging systems based on colour CCD cameras, giving rise to estimated tristimulus values dependent of the illuminant. This property of the spectral sensitivities motivates the use of multispectral imaging systems, since the only way to assure a colour matching for all observers and under changes in illumination is achieving a spectral matching. The most direct method to obtain spectral information of the measured samples is to increase the sampling over the three traditional acquisition channels by means of narrowband filters, which is known as a multispectral imaging system. The application fields of the multispectral imaging systems have increased enormously in last years, fundamentally due to the possibility that offer of estimating accurately the reflectance spectrum at each pixel and, from it, the XYZ tristimulus values avoiding metamerism.The multispectral imaging system designed and developed in this work comprises a monochrome 12-bits cooled CCD camera, a motorized filter wheel controlled via software with a set of narrowband filters, and an objective lens of variable focal length. A set of seven narrowband interference filters covering the whole visible range of the spectrum, with equal FWHM and equidistant central wavelengths, are used following the results obtained in previous works in the NIR region of the spectrum, and extrapolating them to the visible range. Each filter constitutes an acquisition channel of the multispectral imaging system, which corresponds to the multispectral configuration of the imaging system mentioned previously.The first stage before an imaging system based on a CCD camera can be used as a measuring instrument with high spatial resolution is to carry out the correction of the different noise sources inherent to the CCD's performance and, especially, the correction of the spatial non-uniformity of the sensor's response. With this aim, the experimental methodology to correct these noise sources has been developed and a linear algorithm for the spatial non-uniformity correction of the system's response has been optimized.Several analyses have also been carried out throughout this work in order to improve the accuracy of the colour measurement and the spectral reconstruction performed using imaging systems based on CCD cameras.Firstly, considering the basic concepts applied in high dynamic range imaging (HDRI) to obtain a device independent representation of the visual content of a real scene, a luminance adaptation model is proposed to increase the dynamic range of the imaging system by taking images at different exposure times in order to obtain useful digital levels for all the pixels. The application of this luminance adaptation model allows to measure colour at each pixel of the image, increasing the dynamic range of the imaging system by this way.Secondly, the influence of the number of samples of the training set on the accuracy of colour measurement and spectral reconstruction is analyzed in order to determine if there exists a relationship between the accuracy of colour measurement and spectral reconstruction, and the size of the training set. Accuracy of system's performance improves by increasing the size of the training set up to 110 colour samples approximately, and becomes independent of the training set used for training sets having a number of colour samples greater or equal to 110.Next, colour measurement and spectral reconstruction performed using both the colorimetric and the multispectral configurations of the imaging system are analyzed depending on the colour ranges measured, i.e. sets of colour samples grouped by their hue property, with the aim of determining if these configurations are especially sensitive to some hues and/or some other colour properties. Firstly, general tendencies are analyzed using the CCDC chart as training and test sets, and secondly, the 1269 colour patches of the Munsell Book of Color - Matte Collection, classified in 10 Munsell hues and each one of these hues in 4 sub-hues, are used to analyze the influence of homogeneity in hue of the training set on system's performance.Homogeneity in hue of the training set is proved to allow improving meaningfully accuracy of system's performance in terms of both colour measurement and spectral reconstruction. On the other hand, three combinations of training and test sets of Munsell's colour patches are used in order to vary the degree of homogeneity in hue of the training set. Best results are obtained using the most homogeneous in hue training sets.Furthermore, results obtained are also analyzed depending on the colour characteristics of samples measured such as the CIELAB coordinates, and the Munsell hue, value and chroma coordinates. No correlation is observed between accuracy of system's performance and the CIELAB coordinates, whereas accuracy of system's performance tends to get worse for samples having Munsell Values V > 7 - 8.The influence of the illuminant used is also analyzed by comparing results obtained using two illuminants: an incandescent lamp illuminant, which is the one used so far, and a D65 simulator illuminant.Then, accuracy of colour measurement and spectral reconstruction is analyzed depending on the reflectance spectra of the colour samples measured, in order to determine if there exists any kind of correlation between them. This study is performed using the best proved combination of system's configuration and illuminant, which is multispectral configuration and D65 simulator illuminant, and the CCDC chart and the Munsell's colour patches as training and test sets. Accuracy of colour measurement and spectral reconstruction is analyzed depending on, on one hand, the Area Under the Curve (AUC) of reflectance spectra and, on the other hand, on the smoothness of the reflectance spectra by means of their Discrete Fourier Transform (DFT), which is usually used in spectrum analysis to determine the smoothness of curves. Considering the AUC analysis, accuracy of colour measurement tends to improve for the colour samples with higher AUCs of their reflectance spectra, whereas this tendency is not observed for the accuracy of spectral reconstruction. However, any direct relationship cannot be established either between the accuracy of colour measurement and the AUC of the reflectance spectra of colour samples. Considering the DFT analysis, accuracy of colour measurement seems to be independent of the shape and/or the smoothness of the reflectance spectra, whereas the best accuracy of spectral reconstruction is frequently associated to a smooth reflectance spectrum, although any general correlation cannot be established between them.Once thoroughly analyzed the multispectral imaging system developed, and established its limitations in terms of accuracy of colour measurement and spectral reconstruction, next stage is determining if any other number and/or combination of commercially available interference filters would allow to improve, at least theoretically, the accuracy of the multispectral imaging system in terms of colour measurement and spectral reconstruction. For this purpose, a simulation study of an optimum multispectral imaging system for colour measurement and spectral reconstruction is presented. This study is performed considering the spectral response of the monochrome 12-bits cooled CCD camera used and a database of commercially available interference filters selected among the databases of Edmund Optics, OptoSigma and CVI. Accuracy of system's performance is improved in terms of accuracy of both colour measurement and spectral reconstruction with an increasing number of interference filters. Nevertheless, this improvement is limited and tends to be insignificant for more than 8 filters. Optimum filters tend to make up for the spectral response of the CCD camera over the whole visible range but considering the drawback the unknown real spectral transmittances of filters supposes (simulations depend greatly on the real spectral transmittances of filters, which not always can be easily simulated from the specifications provided by suppliers), the selection of a set of interference filters having equidistant peak positions covering the whole visible range, equal FWHMs that allow a slight overlapping between them, and the higher transmittance possible, as it was done in this work, constitutes an acceptable option to obtain a worthy multispectral imaging system.Finally, the applicability of the multispectral imaging system developed is tested not only using standardized colour charts, such as the CCCR, CCDC, and the Munsell's colour patches used so far, but also using real samples, such as a set of 56 textile samples grouped in 28 pairs, which were made specifically to test the applicability of colour difference formulas, and the D65 simulator illuminant. Different combinations of training and test sets are analyzed. Best results are obtained, in average, using training sets homogeneous in hue and carrying out a previous hue classification of the textile samples used as test set. Moreover, the multispectral imaging system developed is proved to be able to detect slight differences both in colour and in reflectance spectra between real samples, making it useful for applications that require discrimination, although a quite low accuracy of system's performance is obtained in detecting both the colour differences and the spectral differences between pairs of textile samples.

<p>The trichromatic principle of representing color has for a long time been dominating in color imaging. The reason is the trichromatic nature of human color vision, but as the characteristics of typical color imaging devices are different from those of human eyes, there is a need to go beyond the trichromatic approach. The interest for multi-channel imaging, i.e. increasing the number of color channels, has made it an active research topic with a substantial potential of application.</p><p>To achieve consistent color imaging, one needs to map the imaging-device data to the device-independent colorimetric representations CIEXYZ or CIELAB, the key concept of color management. As the color coordinates depend not only on the reflective spectrum of the object but also on the spectral properties of the illuminant, the colorimetric representation suffers from metamerism, i.e. objects of the same color under a specific illumination may appear different when they are illuminated by other light sources. Furthermore, when the sensitivities of the imaging device differ from the CIE color matching functions, two spectra that appear different for human observers may result in identical device response. On contrary, in multispectral imaging, color is represented by the object’s physical characteristics namely the spectrum which is illuminant independent. With multispectral imaging, different spectra are readily distinguishable, no matter they are metameric or not. The spectrum can then be transformed to any color space and be rendered under any illumination.</p><p>The focus of the thesis is high quality image-acquisition in colorimetric and multispectral formats. The image acquisition system used is an experimental system with great flexibility in illumination and image acquisition setup. Besides the conventional trichromatic RGB filters, the system also provides the possibility of acquiring multi-channel images, using 7 narrowband filters. A thorough calibration and characterization of all the components involved in the image acquisition system is carried out. The spectral sensitivity of the CCD camera, which can not be derived by direct measurements, is estimated using least squares regression, optimizing the camera response to measured spectral reflectance of carefully selected color samples.</p><p>To derive mappings to colorimetric and multispectral representations, two conceptually different approaches are used. In the model-based approach, the physical model describing the image acquisition process is inverted, to reconstruct spectral reflectance from the recorded device response. In the empirical approach, the characteristics of the individual components are ignored, and the functions are derived by relating the device response for a set of test colors to the corresponding colorimetric and spectral measurements, using linear and polynomial least squares regression.</p><p>The results indicate that for trichromatic imaging, accurate colorimetric mappings can be derived by the empirical approach, using polynomial regression to CIEXYZ and CIELAB. Because of the media-dependency, the characterization functions should be derived for each combination of media and colorants. However, accurate spectral data reconstruction requires for multi-channel imaging, using the model-based approach. Moreover, the model-based approach is general, since it is based on the spectral characteristics of the image acquisition system, rather than the characteristics of a set of color samples.</p> / Report code: LiU-TEK-LIC- 2006:70

A novel imaging technology, digital breast tomosynthesis (DBT), is a technique that overcomes the tissue superposition limitation of conventional mammography by acquiring a limited number of X-ray projections from a narrow angular range, and combining these projections to reconstruct a pseudo-3D image. The emergence of DBT as a potential replacement or adjunct to mammographic screening mandates that solutions be found to two of its major limitations, namely X-ray scatter and mono-energetic reconstruction methods. A multi-faceted software-based approach to enhance the image quality of DBT imaging has the potential to increase the sensitivity and specificity of breast cancer detection and diagnosis. A scatter correction (SC) algorithm and a spectral reconstruction (SR) algorithm are both ready for implementation and clinical evaluation in a DBT system and exhibit the potential to improve image quality. A principal component analysis (PCA) based model of breast shape and a PCA model of X-ray scatter optimize the SC algorithm for the clinical realm. In addition, a comprehensive dosimetric characterization of a FDA approved DBT system has also been performed, and the feasibility of a new dual-spectrum, single-acquisition DBT imaging technique has also been evaluated.

Em radioterapia, o espectro de energia é o componente mais importante dos feixes de elétrons. Espectros de energia de elétrons são relevântes para o cálculo acurado da dose, aplicações do sistema de planejamento e simulações realistas. Reconstrução inversa consiste na derivação do espectro de energia de elétrons a partir de curvas de porcentagem de dose em profundidade utilizando um apropiado modelo matemático. Reconstrução inversa é considerada a melhor dentre muitas abordagens porque: i) não requer nenhum equipamento suplementar ou do conhecimento detalhado da geometria e composição do cabeçote do acelerador; ii) equipamentos para a medição de curvas de porcentagem de dose em profundidade estão disponíveis em qualquer clínica e iii) é computacionalmente rápida. Neste trabalho, usou-se o método de reconstrução inversa baseado na sinergia recozimento simulado generalizado-regularização de Tikhonov. A validação da reconstrução foi realizada através do índice gama sob critérios clínicos de aceitação restritivos. Resultados mostraram que os espectros de energia reconstruídos reproduzem com precisão a porcentagem de dose em profundidade clínica bem como valores de dose fora do eixo central. Assim, concluí-se que o método empregado é ecaz para reconstruir espectros de energia que representam efetivamente espectros de energia do acelerador que atingem na supercie do fantoma. Consequentemente, sob certos limites, eles poderiam auxiliar em simulações realistas do tratamento. / In radiotherapy, energy spectrum is the most critical component of any electron beam. Knowledge of energy spectrum is important for accurate dose calculation, treatment planning applications and realistic simulations. Inverse reconstruction derives energy spectrum from the measured percentage depth dose using an appropriate mathematical model. There are several advantages to using inverse reconstruction: i) it does not require any supplementary equipment or detailed knowledge of the geometry head and composition; ii) the equipment for measurement of the percentage depth dose is standard and already available in any clinic and iii) it is computationally fast. In this work, we used the inverse reconstruction method based on the synergy simulated annealing generalized-Tikhonov regularization. Validation of inverse reconstruction was done by comparing the measured and reconstructed percentage depth dose via the gamma index. Results show the reconstructed electron energy spectra accurately reproduce the clinical dose percentage as well as o-axis dose values. Therefore, it was concluded that the method employed is eective to reconstruct energy spectra that eectively represent accelerator energy spectra reaching the phantom surface. Consequently, under certain limits, they could aid in realistic simulations of treatment.

Em radioterapia, o espectro de energia é o componente mais importante dos feixes de elétrons. Espectros de energia de elétrons são relevântes para o cálculo acurado da dose, aplicações do sistema de planejamento e simulações realistas. Reconstrução inversa consiste na derivação do espectro de energia de elétrons a partir de curvas de porcentagem de dose em profundidade utilizando um apropiado modelo matemático. Reconstrução inversa é considerada a melhor dentre muitas abordagens porque: i) não requer nenhum equipamento suplementar ou do conhecimento detalhado da geometria e composição do cabeçote do acelerador; ii) equipamentos para a medição de curvas de porcentagem de dose em profundidade estão disponíveis em qualquer clínica e iii) é computacionalmente rápida. Neste trabalho, usou-se o método de reconstrução inversa baseado na sinergia recozimento simulado generalizado-regularização de Tikhonov. A validação da reconstrução foi realizada através do índice gama sob critérios clínicos de aceitação restritivos. Resultados mostraram que os espectros de energia reconstruídos reproduzem com precisão a porcentagem de dose em profundidade clínica bem como valores de dose fora do eixo central. Assim, concluí-se que o método empregado é ecaz para reconstruir espectros de energia que representam efetivamente espectros de energia do acelerador que atingem na supercie do fantoma. Consequentemente, sob certos limites, eles poderiam auxiliar em simulações realistas do tratamento. / In radiotherapy, energy spectrum is the most critical component of any electron beam. Knowledge of energy spectrum is important for accurate dose calculation, treatment planning applications and realistic simulations. Inverse reconstruction derives energy spectrum from the measured percentage depth dose using an appropriate mathematical model. There are several advantages to using inverse reconstruction: i) it does not require any supplementary equipment or detailed knowledge of the geometry head and composition; ii) the equipment for measurement of the percentage depth dose is standard and already available in any clinic and iii) it is computationally fast. In this work, we used the inverse reconstruction method based on the synergy simulated annealing generalized-Tikhonov regularization. Validation of inverse reconstruction was done by comparing the measured and reconstructed percentage depth dose via the gamma index. Results show the reconstructed electron energy spectra accurately reproduce the clinical dose percentage as well as o-axis dose values. Therefore, it was concluded that the method employed is eective to reconstruct energy spectra that eectively represent accelerator energy spectra reaching the phantom surface. Consequently, under certain limits, they could aid in realistic simulations of treatment.

The trichromatic principle of representing color has for a long time been dominating in color imaging. The reason is the trichromatic nature of human color vision, but as the characteristics of typical color imaging devices are different from those of human eyes, there is a need to go beyond the trichromatic approach. The interest for multi-channel imaging, i.e. increasing the number of color channels, has made it an active research topic with a substantial potential of application. To achieve consistent color imaging, one needs to map the imaging-device data to the device-independent colorimetric representations CIEXYZ or CIELAB, the key concept of color management. As the color coordinates depend not only on the reflective spectrum of the object but also on the spectral properties of the illuminant, the colorimetric representation suffers from metamerism, i.e. objects of the same color under a specific illumination may appear different when they are illuminated by other light sources. Furthermore, when the sensitivities of the imaging device differ from the CIE color matching functions, two spectra that appear different for human observers may result in identical device response. On contrary, in multispectral imaging, color is represented by the object’s physical characteristics namely the spectrum which is illuminant independent. With multispectral imaging, different spectra are readily distinguishable, no matter they are metameric or not. The spectrum can then be transformed to any color space and be rendered under any illumination. The focus of the thesis is high quality image-acquisition in colorimetric and multispectral formats. The image acquisition system used is an experimental system with great flexibility in illumination and image acquisition setup. Besides the conventional trichromatic RGB filters, the system also provides the possibility of acquiring multi-channel images, using 7 narrowband filters. A thorough calibration and characterization of all the components involved in the image acquisition system is carried out. The spectral sensitivity of the CCD camera, which can not be derived by direct measurements, is estimated using least squares regression, optimizing the camera response to measured spectral reflectance of carefully selected color samples. To derive mappings to colorimetric and multispectral representations, two conceptually different approaches are used. In the model-based approach, the physical model describing the image acquisition process is inverted, to reconstruct spectral reflectance from the recorded device response. In the empirical approach, the characteristics of the individual components are ignored, and the functions are derived by relating the device response for a set of test colors to the corresponding colorimetric and spectral measurements, using linear and polynomial least squares regression. The results indicate that for trichromatic imaging, accurate colorimetric mappings can be derived by the empirical approach, using polynomial regression to CIEXYZ and CIELAB. Because of the media-dependency, the characterization functions should be derived for each combination of media and colorants. However, accurate spectral data reconstruction requires for multi-channel imaging, using the model-based approach. Moreover, the model-based approach is general, since it is based on the spectral characteristics of the image acquisition system, rather than the characteristics of a set of color samples. / Report code: LiU-TEK-LIC- 2006:70

L’évaluation visuelle de lésions cutanées est l’analyse la plus couramment réalisée par les dermatologues. Ce diagnostic s’effectue principalement à l’œil nu et se base sur des critères tels que la taille, la forme, la symétrie mais principalement la couleur. Cependant, cette analyse est subjective car dépendante de l’expérience du praticien et des conditions d’utilisation. Nous proposons dans ce manuscrit (1) le développement d’une caméra multispectrale spécialement conçue pour un usage en dermatologie. Cette caméra multispectrale se base sur la technologie de roue porte-filtres composée de filtres interférentiels et d’un algorithme basé sur les réseaux de neurones générant un cube hyperspectral de données cutanées. Cet ensemble combine l’avantage d’un spectrophotomètre (information spectrale), et celui d’une caméra (information spatiale). Son intérêt est également de délivrer une information reproductible et indépendante des conditions d’acquisition. La mise en place d’un protocole d’acquisition de données de peaux saines issues de cinq des six phototypes existants a permis la validation de notre système en comparant les spectres générés par notre système avec des spectres théoriques acquis par un spectrophotomètre professionnel. (2) La réflectance spectrale de données de peau fournit une information précieuse, car directement liée à sa composition en chromophores. La mesure quantitative des propriétés optiques du tissu cutané peut être basée sur la modélisation de la propagation de la lumière dans la peau. Pour cela, nous nous sommes appuyés sur le modèle de Kubelka-Munk, auquel nous avons associé une méthode d’optimisation basée sur les algorithmes évolutionnaires. Cette dernière apporte une réponse à l’inversion de ce modèle. A partir de cette approche, la quantification de divers paramètres de la peau peut être obtenue, tels que la mélanine et l’hémoglobine. (3) La validation de cette méthodologie est effectuée sur des données pathologiques (vitiligo et melasma) et permet de quantifier une différence de composition entre zone saine et zone affectée sur une même image. / Visual evaluation of cutaneous lesions is the analysis the most commonly performedby dermatologists. This diagnostic is mainly done by naked eye and is based on criterionsuch as the size, shape, symmetry but principally on colour of the lesions. However, thisanalysis is subjective because it depends on the practician experience and the acquisitionconditions. We propose in this dissertation (1) the development of a multispectralcamera specifically dedicated for dermatological use. This device is based on a filterwheel composed of interferential filters and a neural network-based algorithm, generatinga hyperspectral cube of cutaneous data. This setting combines advantage of both spectrophotometer(spectral information) and digital camera (spatial information). Its maininterest is also to provide reproducible information which is independent of the acquisitionconditions. The setting-up of an acquisition protocol of healthy skin data from five of thesix exisiting skin phototypes allows the validation of our system by comparing spectragenerated by our system and theoretical spectra acquired by professional spectrophotometer.(2) Skin spectral reflectance provides precious information because it is directly linkedto the skin chromophore composition. Quantitative measure of cutaneous tissue opticalproperties can be based on the modelisation of light propagation in skin. For this purpose,we based our method on Kubelka-Munk model with which we associated an optimizationmethod based on evolutionary algorithm. This method helps for the model inversion.Using this approach, quantification of diverse parameters of skin can be obtained such asmelanin and haemoglobin. (3) The validation of this model is performed on disease skindata (vitiligo and melasma) and allows to quantify difference between healthy and affectedskin area within a single image.

Für Entwurf, Modellierung sowie Überwachung von Gasphasenprozessen sind fun-dierte Kenntnisse über elementare Zustandsgrößen wie Temperatur oder Spezieskon-zentration unerlässlich. Obwohl bereits heute eine breite Palette an optischen, nicht-invasiven Online-Messtechniken zu Verfügung steht, ist deren Einsatz noch immer auf wenige Anwendungsfelder beschränkt. Die Gründe dafür liegen im oft hohen ex-perimentellen Aufwand oder in anderen Nachteilen wie der Notwendigkeit zum Einsatz von Tracern oder der Kalibrierung über zusätzliche Referenzen. Um diese Nachteile zu umgehen, wurde im Rahmen dieser Arbeit ein mobiles, faserbasiertes Sensorsystem, basierend auf der spontanen Raman-Spektroskopie entwickelt. Die Technik verwendet durchstimmbare NIR-Dauerstrich-Laser-Anregung, Signalerfassung in rückstreuender Geometrie (Punktmessung) und erfordert weder Probennahme, noch Tracer innerhalb der Strömung oder Kalibrierschritte am zu untersuchenden Prozess. Die Methode ermöglicht die simultane Bestimmung von Gastemperaturen und Spezieskonzentrationen sowie im Falle von Aerosolen die Bestimmung der Partikelspezies und der Anteile ihrer polymorphen Kristallstrukturen. Die Datenauswertung basiert auf der Rekonstruktion der gemessenen Spektren anhand simulierter Modellspektren durch Least-Square-Algorithmen. Herkömmliche Ansätze liefern lediglich Parameter, die das Residuum zwischen Simulation und Messsignal minimieren. Unsicherheiten der Messgrößen sind daraus nicht ermittelbar und werden deshalb konventionell durch Wiederholung der Messung bestimmt. Mit Hilfe der hier eingesetzten Bayes'schen Statistik lassen sich die entsprechenden Unsicherheiten direkt bestimmen. Darüber hinaus ermöglicht der Ansatz das Einbeziehen von Vorwissen zur Verbesserung der Robustheit und Genauigkeit der Auswertung. Die Performance des Sensorsystems wurde durch Einsätze an verschiedenen Gasphasenprozessen getestet und evaluiert. Dazu gehören Test-Aerosole, ein TiO2-Nanopartikelsyntheseprozess sowie eine laminare, rußarme Flamme. Ein leicht modifiziertes Sensorsystem (VIS-Anregung) wurde an einem Vergasungsreaktor eingesetzt. Generell konnte eine hohe Qualität der ermittelten Messgrößen festgestellt werden. So sind deren Unsicherheiten mit denen deutlich komplexerer Messtechniken vergleichbar, stellenweise sogar geringer. Die mittlere Unsicherheit der Gastemperaturen innerhalb der Flamme betrug nur 1,6 %. Somit ermöglicht der vorgestellte Sensor bei geringem experimentellen Aufwand die Bestimmung wertvoller Prozessdaten und stellt so potentiell die Basis für eine breitere Anwendung optischer Prozessmesstechnik dar. / For the design, modelling and monitoring of gas-phase processes a profound knowledge of elementary state variables such as temperature or species concentration is essential. Although a wide range of optical, non-invasive online measurement techniques is already available today, their use is still limited to a few fields of application. The reasons for this are the regularly high experimental effort or other disadvantages such as the necessity to use tracers or to execute calibration via additional references. In order to avoid these disadvantages, a mobile, fiber-based sensor system based on spontaneous Raman spectroscopy was developed within the scope of this work. The technique uses tunable NIR continuous-wave laser excitation, signal acquisition in backscattering geometry (point measurement) and requires neither sampling, tracers within the flow nor calibration steps at the process under investigation. The method allows the simultaneous determination of gas temperatures and species concentrations and, in the case of aerosols, the determination of the particle species and their polymorphic crystal structures. The data evaluation is based on the reconstruction of the measured spectra using simulated model spectra through least square algorithms. Conventional approaches only provide parameters that minimize the residual between simulation and measurement signal. Uncertainties of the measured variables cannot be determined from these parameters and are, therefore, determined conventionally by repeating the measurement. With the help of the Bayesian statistics used here, the corresponding uncertainties can be determined directly. Furthermore, the approach allows the inclusion of prior knowledge to improve the robustness and accuracy of the evaluation. The performance of the sensor system was tested and evaluated by using it in different gas phase processes. These include test aerosols, a TiO2 nanoparticle synthesis process and a laminar weakly sooting flame. A slightly modified system (VIS excitation) was used with a similar operation strategy at a gasification reactor. In general, a high quality of the measured variables could be determined. Their uncertainties are comparable with those of much more complex measuring techniques, in some cases even lower. The mean uncertainty of the gas temperatures within the flame was only 1.6 %. Thus, the presented sensor enables the determination of valuable process data with low experimental effort and can potentially be the basis for a broader application of optical process measurement technology.