In the terrestrial biosphere forests have a significant role as a carbon sink. Under recent climate change, it is increasingly important to detect seasonal change or ‘phenology’ that can influence the global carbon cycle. Monitoring canopies using camera systems has offered an inexpensive means to quantify the phenological changes. However, the reliability is not well known. In order to examine the usefulness of cameras to observe forest phenology, we analysed canopy images taken in two deciduous forests in Japan and England and investigate which colour index is best for tracking forest phenology and predict carbon uptake by trees. A camera test using model leaves under controlled conditions has also carried out to examine sensitivity of colour indices for discriminating leaf colours. The main findings of the present study are: 1) Time courses of colour indices derived from images taken in deciduous forests showed typical patterns throughout the growing season. Although cameras are not calibrated instrument, analysis of images allowed detecting the timings of phenological events such as leaf onset and leaf fall; 2) The strength of the green channel (or chromatic coordinate of green) was useful to observe leaf expansion as well as damage by spring late frost. However, the results of the camera test using model leaves suggested that this index was not sufficiently sensitive to detect leaf senescence. Amongst colour indices, Hue was the most robust metric for different cameras, different atmospheric conditions and different distances. The test also revealed Hue was useful to track nitrogen status of leaves; 3) Modelling results using a light use efficiency model for GPP showed a strong relationship between GPP and Hue, which was stronger than the relationships using alternative traditional indices.

In this thesis, it is proposed to get the high definition color images by using super &ndash / resolution algorithms. Resolution enhancement of RGB, HSV and YIQ color domain images is presented. In this study, three solution methods are presented to improve the resolution of HSV color domain images. These solution methods are suggested to beat the color artifacts on super resolution image and decrease the computational complexity in HSV domain applications. PSNR values are measured and compared with the results of other two color domain experiments. In RGB color space, super &ndash / resolution algorithms are applied three color channels (R, G, B) separately and PSNR values are measured. In YIQ color domain, only Y channel is processed with super resolution algorithms because Y channel is luminance component of the image and it is the most important channel to improve the resolution of the image in YIQ color domain. Also, the third solution method suggested for HSV color domain offers applying super resolution algorithm to only value channel. Hence, value channel carry brightness data of the image. The results are compared with the YIQ color domain experiments. During the experiments, four different super resolution algorithms are used that are Direct Addition, MAP, POCS and IBP. Although, these methods are widely used reconstruction of monochrome images, here they are used for resolution enhancement of color images. Color super resolution performances of these algorithms are tested.

The diploma thesis is dividend into four parts. The first part describes basic terms in video technology (luminance, hue, diagrams CIE). The second part includes types of colour spaces RGB, HSV, CMY(K), YUV, YCbCr, YIQ. In the third and fourth part, these theoretical findings are used to propound laboratory observations. The laboratory observation processes the colour rendition of the colours in video technology. In the Matlab software, a user system environment was developed for operations with measured values. The software is capable of recalculating chromaticity coordinates between different colour spaces, to screen colours into diagrams CIE and to show the vectors of colours. The device used for measuring was Chromametr Konica Minolta CS-100A. A manual for the device was created. The laboratory observation was measured and processed in the form of a laboratory protocol.

This Master Thesis, inspired by the relevance that home-offices have assumed as a consequence of the COVID-19 pandemic, originated from the architectural, quantitative, and qualitative analysis of lighting within the author’s student accommodation on KTH Main Campus, in Stockholm (Sweden). As a matter of fact, this background study proved that recommended lighting levels (Illuminance, Contrast Ratio, CCT, CRI, M-EDI, and DER values) were not met, making the space unsuitable and unhealthy to both live and work in. Moreover, evaluating individual lighting preferences, it was demonstrated that flexibility, customizability, and adaptability to daylighting and tasks are fundamental requirements for working from home.Considering the temporary nature of students’ leases, the idea of developing an inexpensive and easily assemblable kit of smart products, aimed at improving lighting in dormitories, came quite naturally.To study the implementation of visual comfort and focus on tasks, literature review, market analysis, quantitative measurements, and hands-on experiments were carried on.Thus, with the gained knowledge and experience, the Home-Office Lighting Kit, an array of commercially available sockets, shades, and smart sources, supporting circadian rhythm and individual preferences, was proposed. Along with it, instructions on set-up and scenarios were provided.Although the overall conclusion was that the market needs products with a better balance between price, sturdiness, and reliability, the lighting conditions within the case study space were substantially improved, making other students interested in doing the same.Eventually, interesting cues for the sector’s development were proposed.

The ideas within this thesis are meant to clarify my explorations, research and painting practice during my studies at Virginia Commonwealth University. I expand on my general statements about being fascinated by advancing technologies and concerned about the after effects of these advancements. The writing explores my curiosity about the internal, skeletal structure of things and how they operate. I explain how the paintings are idiosyncratic hybrids that evoke animation, imaginary scientific propositions, blueprints, maps, and advancing technologies. The work combines these interests with my observations of day-to-day experiences. Isolated events provide found compositions which I then manipulate: a seemingly mundane bike ride gets mapped into a well–ordered schematic of social interaction.

Der Einsatz von Bildern in den unterschiedlichsten Bereichen ist enorm gestiegen, da Bilder die Fähigkeit haben Erlebnisse, sowie Emotionen zu erzeugen und die Phantasie anzuregen. Zudem lässt die rasante Entwicklung im Multimediabereich die Anzahl der fotografierten und gespeicherten Bilder steigen. Die Suche nach dem „besten Bild“ für z.B. eine Kampagne gestaltet sich schwierig, da die Inhalte mehrerer Bilder zu einem Thema nicht selten eine hohe Ähnlichkeit aufweisen. Die Bilder können sich allerdings sehr deutlich in ihren Low-Level Features, wie Farbton, Sättigung und Helligkeit, unterscheiden. Jedoch ist der Emotional Gap zwischen diesen Low-Level Features und der dahinter steckenden High-Level-Semantik im inhaltsbasierten Image Retrieval nur marginal untersucht. Im Fokus dieser Arbeit steht die Analyse des Einflusses der emotionalen Wirkung eines Bildes auf die Qualität der Image Retrieval Ergebnisse. Dies umfasst zum einen die Untersuchung der von Farbeigenschaften eines Bildes ausgelösten Emotionen, sowie die Evaluation der Ergebnisse einer emotionalen Bildsuche. Durch verschiedene Experimente kann gezeigt werden, dass die Helligkeit und der Farbton die emotionale Wahrnehmung eines Bildes maßgeblich beeinflussen. Anhand der Ergebnisse konnte eine emotionale Annotation von Bildern und somit die Einbindung von Emotionen in den Suchprozess ermöglicht werden. Die anschließende Evaluierung der Suchergebnisse zeigt, dass die Qualität der Ergebnisse des Image Retrievals verbessert werden konnte. / The use of pictures in a variety of areas has increased tremendously in recent years, as they stimulate a person’s imagination and help to create first experiences and emotions. Furthermore, the rapid developments in multimedia have led to an escalation of the number of digitally stored pictures and photographs. Consequently, finding the ‘best picture’ for a convincing advertising campaign has been becoming increasingly difficult due to the abundance of available pictures. To further complicate this search process, a lot of pictures related to a specific topic are very similar with regard to their content. However, their low-level features, such as hue, saturation, and luminance, might differ considerably. Therefore, this work focusses on the influence of emotional characteristics on the image retrieval process. This includes the study of emotions caused by the color properties of a picture, as well as the evaluation of the results of an emotional image retrieval processes. Results of different experiments show that a picture’s luminance and color have the power to influence emotion. The subsequent evaluation of the results shows an improvement of emotional image retrieval processes. Consequently, one can conclude that the consideration of emotions for ranking affects the quality of the results of the Image Retrieval positively.

This thesis describes the principles of making application which is able to set and control camera. The first part describes basic camera connections and it explains definition and specification of camera’s features. The second part of my thesis describes implementation of application, which can use more cameras to image preview, image acquisition and to simply set of camera’s features. To implement the applications we can use MATLAB and C++BUILDER uses opencv libraries.

Der Einsatz von Bildern in den unterschiedlichsten Bereichen ist enorm gestiegen, da Bilder die Fähigkeit haben Erlebnisse, sowie Emotionen zu erzeugen und die Phantasie anzuregen. Zudem lässt die rasante Entwicklung im Multimediabereich die Anzahl der fotografierten und gespeicherten Bilder steigen. Die Suche nach dem „besten Bild“ für z.B. eine Kampagne gestaltet sich schwierig, da die Inhalte mehrerer Bilder zu einem Thema nicht selten eine hohe Ähnlichkeit aufweisen. Die Bilder können sich allerdings sehr deutlich in ihren Low-Level Features, wie Farbton, Sättigung und Helligkeit, unterscheiden. Jedoch ist der Emotional Gap zwischen diesen Low-Level Features und der dahinter steckenden High-Level-Semantik im inhaltsbasierten Image Retrieval nur marginal untersucht. Im Fokus dieser Arbeit steht die Analyse des Einflusses der emotionalen Wirkung eines Bildes auf die Qualität der Image Retrieval Ergebnisse. Dies umfasst zum einen die Untersuchung der von Farbeigenschaften eines Bildes ausgelösten Emotionen, sowie die Evaluation der Ergebnisse einer emotionalen Bildsuche. Durch verschiedene Experimente kann gezeigt werden, dass die Helligkeit und der Farbton die emotionale Wahrnehmung eines Bildes maßgeblich beeinflussen. Anhand der Ergebnisse konnte eine emotionale Annotation von Bildern und somit die Einbindung von Emotionen in den Suchprozess ermöglicht werden. Die anschließende Evaluierung der Suchergebnisse zeigt, dass die Qualität der Ergebnisse des Image Retrievals verbessert werden konnte. / The use of pictures in a variety of areas has increased tremendously in recent years, as they stimulate a person’s imagination and help to create first experiences and emotions. Furthermore, the rapid developments in multimedia have led to an escalation of the number of digitally stored pictures and photographs. Consequently, finding the ‘best picture’ for a convincing advertising campaign has been becoming increasingly difficult due to the abundance of available pictures. To further complicate this search process, a lot of pictures related to a specific topic are very similar with regard to their content. However, their low-level features, such as hue, saturation, and luminance, might differ considerably. Therefore, this work focusses on the influence of emotional characteristics on the image retrieval process. This includes the study of emotions caused by the color properties of a picture, as well as the evaluation of the results of an emotional image retrieval processes. Results of different experiments show that a picture’s luminance and color have the power to influence emotion. The subsequent evaluation of the results shows an improvement of emotional image retrieval processes. Consequently, one can conclude that the consideration of emotions for ranking affects the quality of the results of the Image Retrieval positively.