Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/232741
Title: A Novel Approach For No_Reference Quality Assessment of Jpeg2000 Images And H_264 Videos Based on Human Visual System
Researcher: SUBRAHMANYAM.CH
Guide(s): D.Venkata Rao, N.Usha Rani
Keywords: Engineering and Technology,Engineering,Instruments and Instrumentation
University: Vignans Foundation for Science Technology and Research
Completed Date: 2016
Abstract: The quality assessment is one of the most intriguing challenges in the media newlineenvironment during the last decade in many applications. The images and videos are newlinecaptured using different devices like handycams, cameras, and mobile phones. The newlinecaptured image and video data is stored in memory and transmitted from one device newlineto other device or accessed from the web. The important task for any image and newlinevideo quality metric is to assess the quality of the image/video on par with human newlinevisual system in subjective judgement. newlineThe quality assessment algorithms are classified in accordance with the information newlineavailable about the original images and videos. The quality assessment can be done by newlineusing Full Reference (FR), Reduced Reference (RR) and No Reference (NR) newlinemethods. The entire original image/video is available as a reference in FR method. FR newlinemethods are based on comparing distorted image/video with the original image/video. newlineRR method is not required to give access to the original image/video but only to newlineprovide representative features about texture or suitable characteristics of the original newlineimage/video. In NR method, image/video quality assessment is done without newlineconsidering the original image/video. In recent years, there has been increasing newlineinterest in the development of NR methods due to the widespread use of multimedia newlineservices in the context of wireless communications and telecommunications systems. newlineIn the last few decades, the quality assessment of the images and videos are based on newlinethe known characteristics of the Human Visual System (HVS). A new paradigm for newlineimage and video quality assessment based on the HVS is highly adopted for distorted newlineimages and videos. No Reference image and video quality assessment algorithms are newlinedeveloped by using machine learning techniques along with human judgements for newlinequality The approach of quality assessment based on product of pairs and their newlinelocalized distortions of adjacent pixels with the difference of one.
Pagination: 115
URI: http://hdl.handle.net/10603/232741
Appears in Departments:Department of Electronics and Communication Engineering

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