Evaluation of the color image and video processing chain and visual quality management for consumer systems

With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video

Perceptual Video Quality Assessment and Enhancement

With the rapid development of network visual communication technologies, digital video has become ubiquitous and indispensable in our everyday lives. Video acquisition, communication, and processing systems introduce various types of distortions, which may have major impact on perceived video quality by human observers. Effective and efficient objective video quality assessment (VQA) methods that can predict perceptual video quality are highly desirable in modern visual communication systems for performance evaluation, quality control and resource allocation purposes. Moreover, perceptual VQA measures may also be employed to optimize a wide variety of video processing algorithms and systems for best perceptual quality. This thesis exploits several novel ideas in the areas of video quality assessment and enhancement. Firstly, by considering a video signal as a 3D volume image, we propose a 3D structural similarity (SSIM) based full-reference (FR) VQA approach, which also incorporates local information content and local distortion-based pooling methods. Secondly, a reduced-reference (RR) VQA scheme is developed by tracing the evolvement of local phase structures over time in the complex wavelet domain. Furthermore, we propose a quality-aware video system which combines spatial and temporal quality measures with a robust video watermarking technique, such that RR-VQA can be performed without transmitting RR features via an ancillary lossless channel. Finally, a novel strategy for enhancing video denoising algorithms, namely poly-view fusion, is developed by examining a video sequence as a 3D volume image from multiple (front, side, top) views. This leads to significant and consistent gain in terms of both peak signal-to-noise ratio (PSNR) and SSIM performance, especially at high noise levels

Efficient global illumination for dynamic scenes

The production of high quality animations which feature compelling lighting effects is computationally a very heavy task when traditional rendering approaches are used where each frame is computed separately. The fact that most of the computation must be restarted from scratch for each frame leads to unnecessary redundancy. Since temporal coherence is typically not exploited, temporal aliasing problems are also more difficult to address. Many small errors in lighting distribution cannot be perceived by human observers when they are coherent in temporal domain. However, when such a coherence is lost, the resulting animations suffer from unpleasant flickering effects. In this thesis, we propose global illumination and rendering algorithms, which are designed specifically to combat those problems. We achieve this goal by exploiting temporal coherence in the lighting distribution between the subsequent animation frames. Our strategy relies on extending into temporal domain wellknown global illumination and rendering techniques such as density estimation path tracing, photon mapping, ray tracing, and irradiance caching, which have been originally designed to handle static scenes only. Our techniques mainly focus on the computation of indirect illumination, which is the most expensive part of global illumination modelling.Die Erstellung von hochqualitativen 3D-Animationen mit anspruchsvollen Lichteffekten ist für traditionelle Renderinganwendungen, bei denen jedes Bild separat berechnet wird, sehr aufwendig. Die Tatsache jedes Bild komplett neu zu berechnen führt zu unnötiger Redundanz. Wenn temporale Koherenz vernachlässigt wird, treten unter anderem auch schwierig zu behandelnde temporale Aliasingprobleme auf. Viele kleine Fehler in der Beleuchtungsberechnung eines Bildes können normalerweise nicht wahr genommen werden. Wenn jedoch die temporale Koherenz zwischen aufeinanderfolgenden Bildern fehlt, treten störende Flimmereffekte auf. In dieser Arbeit stellen wir globale Beleuchtungsalgorithmen vor, die die oben genannten Probleme behandeln. Dies erreichen wir durch Ausnutzung von temporaler Koherenz zwischen aufeinanderfolgenden Einzelbildern einer Animation. Unsere Strategy baut auf die klassischen globalen Beleuchtungsalgorithmen wie "Path tracing", "Photon Mapping" und "Irradiance Caching" auf und erweitert diese in die temporale Domäne. Dabei beschränken sich unsereMethoden hauptsächlich auf die Berechnung indirekter Beleuchtung, welche den zeitintensivsten Teil der globalen Beleuchtungsberechnung darstellt