Paper
18 January 2004 Edge degradation for objective video quality metrics
Chulhee Lee, Sungdeuk Cho, Jihwan Choe, Taewook Jung, Wonsoek Ahn
Author Affiliations +
Proceedings Volume 5308, Visual Communications and Image Processing 2004; (2004) https://doi.org/10.1117/12.529804
Event: Electronic Imaging 2004, 2004, San Jose, California, United States
Abstract
In this paper, we propose a new method for an objective measurement of video quality based on edge degradation. One of the most important requirements for an objective method for video quality measurement is that it should provide consistent performances over a wide range of video sequences that are not used in the designing stage. By analyzing subjective scores of various video sequences, we found that the human visual system is sensitive to degradation around edges. In other words, when edge areas of a video are blurred, evaluators tend to give low scores to the video even though the overall mean squared error is not so large. Based on this observation, we propose an objective video quality measurement method that measures degradation around edges. In the proposed method, we first apply an edge detection algorithm to videos and find edge areas. Then, we measure degradation of those edge areas by computing mean squared error. From this mean squared error, we compute the PSNR and use it as video quality metric. Experimental results show that the proposed method compares favorably with the current objective methods for video quality measurement. Furthermore, when the proposed method is applied to test video sequences that are not used in the designing stage, it still consistently provides satisfactory performances.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chulhee Lee, Sungdeuk Cho, Jihwan Choe, Taewook Jung, and Wonsoek Ahn "Edge degradation for objective video quality metrics", Proc. SPIE 5308, Visual Communications and Image Processing 2004, (18 January 2004); https://doi.org/10.1117/12.529804
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Video

Video processing

Quality measurement

Image processing

Edge detection

Detection and tracking algorithms

Visual system

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