Operadores de tone mapping reverso (RTMOs) realçam imagens e vídeos de baixa faixa dinâmica para visualização em monitores de alta faixa dinâmica. Um problema comum encontrado por operadores anteriores é a maneira com que tratam conteúdo sub ou superexposto. Sob tais condições, eles podem não ser eficientes, e até mesmo causar perda e reversão de contraste visível. Apresentamos uma classe de operadores de tone mapping reverso, baseados no filtro bilateral cruzado (cross bilateral filter), capazes de gerar imagens HDR de alta qualidade. Experimentos utilizando uma métrica objetiva de avaliação de imagens demostram que nosso método é a única técnica capaz de realçar detalhes perceptíveis ao longo de uma grande gama de exposições de imagem, a qual inclui desde imagens subexpostas até imagens superexpostas. / Reverse tone mapping operators (rTMOs) enhance low-dynamic-range images and videos for display on high dynamic range monitors. A common problem faced by previous rTMOs is the handling of under or overexposed content. Under such conditions, they may not be effective, and even cause loss and reversal of visible contrast. We present a class of local rTMOs based on cross bilateral filtering that is capable of generating highquality HDR images and videos for a wide range of exposure conditions. Experiments performed using an objective image quality metric show that our approach is the only single technique available that can gracefully enhance perceived details across a large range of image exposures.

<p>Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. The methods are trained with examples instead of explicitely designing the appearance of the visualization.</p><p>This approach is exemplified using two applications. In the fist the problem to compute an image of the sky for dynamic weather, that is taking account of the current weather state, is addressed. It is a complicated problem to tie the appearance of the sky to a weather state. The method is trained with weather data sets and images of the sky to be able to synthesize a sky image for arbitrary weather conditions. The method has been trained with various kinds of weather and images data. The results show that this is a possible method to construct weather visaualizations, but more work remains in characterizing the weather state and further refinement is required before the full potential of the method can be explored. This approach would make it possible to synthesize sky images of dynamic weather using a fast and efficient empirical method.</p><p>In the second application the problem of computing synthetic satellite images form numerical forecast data sets is addressed. In this case a mode is trained with preclassified satellite images and forecast data sets to be able to synthesize a satellite image representing arbitrary conditions. The resulting method makes it possible to visualize data sets from numerical weather simulations using synthetic satellite images, but could also be the basis for algorithms based on a preliminary cloud classification.</p> / Report code: LiU-Tek-Lic-2004:66.

We describe the design and implementation of a high dynamic range (HDR) imaging system capable of capturing RGB color images with a dynamic range of 10,000,000 : 1 at 25 frames per second. We use a highly programmable camera unit with high throughput A/D conversion, data processing and data output. HDR acquisition is performed by multiple exposures in a continuous rolling shutter progression over the sensor. All the different exposures for one particular row of pixels are acquired head to tail within the frame time, which means that the time disparity between exposures is minimal, the entire frame time can be used for light integration and the longest expo- sure is almost the entire frame time. The system is highly configurable, and trade-offs are possible between dynamic range, precision, number of exposures, image resolution and frame rate.

With the growing demand of embedded graphics applications, how to provide an efficient graphics hardware acceleration solution has drawn much attention. It is well known that computer graphics contains two major domains: two-dimensional (2D) and three-dimensional (3D) graphics. Each domain owns large amounts of applications, such that general embedded platforms will require both graphics acceleration supports. This thesis proposes an advanced texture unit architecture which can provide various 3D texture filtering functions including trilinear, anistrophics filtering etc , and 2D coloring, painting, and texturing functions. Our proposed design consists of a core computation unit, and a set of data registers. The equations for those supported functions are decomposed into a series of basic arithmetic operations such as multiply-add-accumulation, multiply, etc executed by the core computation unit. To evaluate those equations for each pixel may require some pre-computed parameters which will be computed outside our unit in advance by the system¡¦s micro-controller. The equations can be computed by our texture unit based on the selected finite-state machine sequences which is stored in the on-chip control table. By updating those sequences can change the functionality provided by our chip. The overall cost of the proposed unit is about 28.36k gates. In addition to various texturing functions, this thesis also proposes an implementation of texture function for high-dynamic range (HDR) textures. HDR textures can provide various color details according to the frame¡¦s global illumination environment. Therefore, the 3D rendering system has to incorporate a tone-mapping mechanism to map the HDR image into normal color range of output display system. To reduce the overall tone-mapping implementation cost, this thesis uses an extra accumulator between the standard per-fragment rendering pipeline stages to accumulate the global illumination intensity based on the depth comparison result of the incoming pixel. After all of the pixels have passed through the pipeline stages, every pixel of the stored rendering result will be fetched into a mapping unit which will generate its mapping color in the normal dynamic range. The overall cost of the additional hardware for the realization of HDR textures is about 6.98k gates.

Today, infrared cameras are used especially for target tracking and surveillance operations. However, they have a high dynamic range output, and the standard display devices cannot handle them. In order to show them on common devices, the dynamic range is cropped. Thus, the contrast of the image is reduced. This is called as the High Dynamic Range (HDR) Compression. Although several algorithms have been proposed for preserving details during the HDR compression process, it cannot be used to enhance the local contrasts of image contents. In this thesis, we compare the performances of contrast enhancement techniques, which are suitable for real time applications. The methods experimented are generally histogram based methods. Some modifications are also proposed in order to reduce computational complexity of the process. Performances of these methods are compared with common objective quality metrics on different image sets.

Typical consumer digital cameras capture the scene by generating a mosaic-like grayscale image, known as a color filter array (CFA) image. One obvious challenge in digital photography is the storage of image, which requires the development of an efficient compression solution. This issue has become more significant due to a growing demand for high dynamic range (HDR) imaging technology, which requires increased bandwidth to allow realistic presentation of visual scene. This thesis proposes two digital camera pipelines, efficiently encoding CFA image data represented in HDR format. Firstly, a lossless compression scheme exploiting a predictive coding followed by a JPEG XR encoding module is introduced. It achieves efficient data reduction without loss of quality. Secondly, a lossy compression scheme that consists of a series of processing operations and a JPEG XR encoding module is introduced. Performance evaluation indicates that the proposed method delivers high quality images at low computational costs.

Typical consumer digital cameras capture the scene by generating a mosaic-like grayscale image, known as a color filter array (CFA) image. One obvious challenge in digital photography is the storage of image, which requires the development of an efficient compression solution. This issue has become more significant due to a growing demand for high dynamic range (HDR) imaging technology, which requires increased bandwidth to allow realistic presentation of visual scene. This thesis proposes two digital camera pipelines, efficiently encoding CFA image data represented in HDR format. Firstly, a lossless compression scheme exploiting a predictive coding followed by a JPEG XR encoding module is introduced. It achieves efficient data reduction without loss of quality. Secondly, a lossy compression scheme that consists of a series of processing operations and a JPEG XR encoding module is introduced. Performance evaluation indicates that the proposed method delivers high quality images at low computational costs.

Zugl.: Koblenz. Landau, Diss., 2007

Ο τομέας της ψηφιακής φωτογράφισης εξελίσσεται διαρκώς. Το γεγονός αυτό, καθιστά τη ψηφιακή φωτογραφία χρήσιμο εργαλείο για διάφορες επιστημονικές και όχι μόνο εφαρμογές. Για αυτό τον λόγο, γίνεται απαραίτητη η λεπτομερέστερη αποτύπωση της πληροφορίας. Η λεπτομερέστερη αποτύπωση της πληροφορίας αποτελεί αντικείμενο της εικονοποίησης υψηλής δυναμικής περιοχής(High Dynamic Range Imaging). Ο σκοπός της παρούσας διπλωματικής εργασίας είναι η μελέτη της εικονοποίησης υψηλής δυναμικής περιοχής και η υλοποίηση ενός αλγορίθμου, κάνοντας χρήση πολλαπλών λήψεων για την παραγωγή τελικής εικόνας με διευρυμένη δυναμική περιοχή. / The field of digital photography is constantly evolving. In fact, this makes digital photography a useful tool in various scientific applications. For this reason, a more detailed presentation of information is needed. The detailed presentation of information is the subject of high dynamic range (High Dynamic Range Imaging). The purpose of this thesis is to study the field of high dynamic range imaging and the implementation of an algorithm, making use of multiple shots to produce a final image with extended dynamic range.

abstract: This study examines the applicability of high dynamic range (HDR) imagery as a diagnostic tool for studying lighting quality in interior environments. It originates from the limitations in lighting quality assessments, particularly from the problematic nature of measuring luminance contrast--a significant lighting quality definer. In this research, HDR imaging method is studied systematically and in detail via extensive camera calibration tests considering the effect of lens and light source geometry (i.e. vignetting, point spread and modulation transfer functions), in-camera variables (i.e. spectral response, sensor sensitivity, metering mode,), and environmental variables (i.e. ambient light level, surface color and reflectance, light source spectral power distribution) on the accuracy of HDR-image-derived luminance data. The calibration test findings are used to create camera setup and calibration guidelines for future research, especially to help minimize errors in image extracted lighting data. The findings are also utilized to demonstrate the viability of the tool in a real world setting--an office environment combining vertical and horizontal tasks. Via the quasi-experimental setup, the relationship between line of sight and perceived luminance contrast ratios are studied using HDR images. Future research can benefit from the calibration guidelines to minimize HDR-based luminance estimation errors. The proposed tool can be used and tested in different contexts and tasks with varying user groups for revising the former luminance-contrast guidelines as well as surface reflectance recommendations. / Dissertation/Thesis / Ph.D. Architecture 2011