Objective Video Quality Assessment Export

@incollection{wang:assessment, abstract = {Digital video data, stored in video databases and distributed through communication networks, is subject to various kinds of distortions during acquisition, compression, processing, transmission, and reproduction. It is imperative for a video service system to be able to realize and quantify the video quality degradations that occur in the system, so that it can maintain, control and possibly enhance the quality of the video data. An effective image and video quality metric is crucial for this purpose. The goal of objective image and video quality assessment research is to design quality metrics that can predict perceived image and video quality automatically. Such a metric can be used to monitor image quality for quality control systems. It can be employed to benchmark image and video processing systems and algorithms. It can also be embedded into an image and video processing system to optimize the algorithms and the parameter settings. This chapter mainly focuses on the basic concepts, ideas and approaches for image and video quality assessment. We first review the background and various implementations of a widely adopted error-sensitivity based philosophy for quality assessment and attempt to point out its limitations. We then introduce a new way to think about the problem of image and video quality assessment and provide some preliminary results of a novel structural distortion based quality assessment method. Next, we introduce the current status of quality assessment research for the cases that the reference images are not or only partially available. We also discuss the issues that are related to the validation of image and video quality metrics, including the recent effort by the video quality experts group (VQEG) in developing, validating and standardizing video quality metrics for television and multimedia applications. Finally, we make some concluding remarks and provide a vision for future directions of image and video quality assessment.}, address = {Boca Raton, FL, USA}, author = {Wang, Zhou and Sheikh, Hamid R. and Bovik, Alan C.}, booktitle = {The Handbook of Video Databases: Design and Applications}, chapter = {41}, citeulike-article-id = {6111499}, citeulike-linkout-0 = {http://www.ece.uwaterloo.ca/~z70wang/publications/QA_hvd_bookchapter.pdf}, editor = {Furht, Borko and Marques, Oge}, isbn = {978-0-8493-7006-9}, keywords = {cs4302, evaluation, multimedia, objective-quality-assessment, perceived-quality, video}, pages = {1041--1078}, posted-at = {2009-11-14 08:03:14}, priority = {2}, publisher = {CRC Press}, title = {Objective Video Quality Assessment}, url = {http://www.ece.uwaterloo.ca/~z70wang/publications/QA_hvd_bookchapter.pdf}, year = {2003} }

TY - CHAP ID - wang:assessment L3 - citeulike-article-id:6111499 N2 - Digital video data, stored in video databases and distributed through communication networks, is subject to various kinds of distortions during acquisition, compression, processing, transmission, and reproduction. It is imperative for a video service system to be able to realize and quantify the video quality degradations that occur in the system, so that it can maintain, control and possibly enhance the quality of the video data. An effective image and video quality metric is crucial for this purpose. The goal of objective image and video quality assessment research is to design quality metrics that can predict perceived image and video quality automatically. Such a metric can be used to monitor image quality for quality control systems. It can be employed to benchmark image and video processing systems and algorithms. It can also be embedded into an image and video processing system to optimize the algorithms and the parameter settings. This chapter mainly focuses on the basic concepts, ideas and approaches for image and video quality assessment. We first review the background and various implementations of a widely adopted error-sensitivity based philosophy for quality assessment and attempt to point out its limitations. We then introduce a new way to think about the problem of image and video quality assessment and provide some preliminary results of a novel structural distortion based quality assessment method. Next, we introduce the current status of quality assessment research for the cases that the reference images are not or only partially available. We also discuss the issues that are related to the validation of image and video quality metrics, including the recent effort by the video quality experts group (VQEG) in developing, validating and standardizing video quality metrics for television and multimedia applications. Finally, we make some concluding remarks and provide a vision for future directions of image and video quality assessment. SN - 978-0-8493-7006-9 AD - Boca Raton, FL, USA EP - 1078 TI - Objective Video Quality Assessment PB - CRC Press T2 - The Handbook of Video Databases: Design and Applications SP - 1041 KW - cs4302 KW - evaluation KW - multimedia KW - objective-quality-assessment KW - perceived-quality KW - video AU - Wang, Zhou AU - Sheikh, Hamid AU - Bovik, Alan A2 - Furht, Borko A2 - Marques, Oge PY - 2003/// UR - http://www.ece.uwaterloo.ca/~z70wang/publications/QA_hvd_bookchapter.pdf ER -