Hybrid video quality prediction: reviewing video quality measurement for widening application scope

A tremendous number of objective video quality measurement algorithms have been developed during the last two decades. Most of them either measure a very limited aspect of the perceived video quality or they measure broad ranges of quality with limited prediction accuracy. This paper lists several perceptual artifacts that may be computationally measured in an isolated algorithm and some of the modeling approaches that have been proposed to predict the resulting quality from those algorithms. These algorithms usually have a very limited application scope but have been verified carefully. The paper continues with a review of some standardized and well-known video quality measurement algorithms that are meant for a wide range of applications, thus have a larger scope. Their individual artifacts prediction accuracy is usually lower but some of them were validated to perform sufficiently well for standardization. Several difficulties and shortcomings in developing a general purpose model with high prediction performance are identified such as a common objective quality scale or the behavior of individual indicators when confronted with stimuli that are out of their prediction scope. The paper concludes with a systematic framework approach to tackle the development of a hybrid video quality measurement in a joint research collaboration.Polish National Centre for Research and Development (NCRD) SP/I/1/77065/10, Swedish Governmental Agency for Innovation Systems (Vinnova

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

Subjective evaluation of de-interlacing techniques

Interlace is part of television standards since the very start of TV-broadcast. The advent of new display principles that cannot handle interlaced video, the wish to up-scale standard definition video for display on large high-definition screens and the introduction of video in traditionally non-interlaced multimedia PCs ask for advanced de-interlacing techniques. Various de-interlacing techniques can be categorized into non-motion compensated methods and motion compensated methods. The former includes linear techniques such as spatial filtering, temporal filtering, vertical-temporal filtering and non-linear techniques like motion adaptive filtering, edge-dependent interpolation, implicitly adapting methods and hybrid methods. The latter category includes temporal backward projection, time-recursive de-interlacing, adaptive-recursive de-interlacing, generalized sampling theorem de-interlacing method and hybrid method. An objective comparison based on Mean Square Error (MSE) and Motion Trajectory Inconsistency (MTI) metric has been given on above listed methods. In this paper, we describe a subjective assessment in which a number of de-interlacing techniques will be ranked by a group of viewers (typically twenty persons). The experiment was set-up according to the recommendations of the ITU. Combined with the objective scores presented in the earlier publications, we then have a thorough analysis of each selected de-interlacing algorithms. This improves the relevance and reliability of our knowledge concerning the performance of these de-interlacing algorithms