Visual Attention Based Video Quality Assessment
碩士 === 國立交通大學 === 多媒體工程研究所 === 103 === Video quality assessment algorithms play an important roles in video processing systems. Since the evaluation by human is much expensive and inconvenient, it is necessary to design an automatic methods that evaluate the quality of videos by computer. Since the...
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ndltd-TW-103NCTU56410332019-05-15T22:33:38Z http://ndltd.ncl.edu.tw/handle/mrd4ev Visual Attention Based Video Quality Assessment 基於視覺注意力的視訊品質評估方法 Yang, Han 楊涵 碩士 國立交通大學 多媒體工程研究所 103 Video quality assessment algorithms play an important roles in video processing systems. Since the evaluation by human is much expensive and inconvenient, it is necessary to design an automatic methods that evaluate the quality of videos by computer. Since the existing image/video quality assessment is not conform to the fact that human beings pay more attention to the important parts of video frames than whole image, we proposed a video quality assessment with utilization of saliency and motion strength in each frame to accurately detect the region that attract human attention. After evaluating with LIVE video quality database which includes different video distortion types, the experimental results show that the proposed algorithm can successfully improve the performance of image quality metrics and video quality assessment at low computation complexity. Peng, Wen-Hsiao 彭文孝 2015 學位論文 ; thesis 30 en_US |
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碩士 === 國立交通大學 === 多媒體工程研究所 === 103 === Video quality assessment algorithms play an important roles in video processing systems. Since the evaluation by human is much expensive and inconvenient, it is necessary to design an automatic methods that evaluate the quality of videos by computer. Since the existing image/video quality assessment is not conform to the fact that human beings pay more attention to the important parts of video frames than whole image, we proposed a video quality assessment with utilization of saliency and motion strength in each frame to accurately detect the region that attract human attention.
After evaluating with LIVE video quality database which includes different video distortion types, the experimental results show that the proposed algorithm can successfully improve the performance of image quality metrics and video quality assessment at low computation complexity.
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Peng, Wen-Hsiao |
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Peng, Wen-Hsiao Yang, Han 楊涵 |
author |
Yang, Han 楊涵 |
spellingShingle |
Yang, Han 楊涵 Visual Attention Based Video Quality Assessment |
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Yang, Han |
title |
Visual Attention Based Video Quality Assessment |
title_short |
Visual Attention Based Video Quality Assessment |
title_full |
Visual Attention Based Video Quality Assessment |
title_fullStr |
Visual Attention Based Video Quality Assessment |
title_full_unstemmed |
Visual Attention Based Video Quality Assessment |
title_sort |
visual attention based video quality assessment |
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2015 |
url |
http://ndltd.ncl.edu.tw/handle/mrd4ev |
work_keys_str_mv |
AT yanghan visualattentionbasedvideoqualityassessment AT yánghán visualattentionbasedvideoqualityassessment AT yanghan jīyúshìjuézhùyìlìdeshìxùnpǐnzhìpínggūfāngfǎ AT yánghán jīyúshìjuézhùyìlìdeshìxùnpǐnzhìpínggūfāngfǎ |
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