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논문 기본 정보

자료유형
학술저널
저자정보
Sankar, Ravi (iCONS Research Group, Dept. of Electrical Engineering, University of South Florida) Ivkovic, Goran (iCONS Research Group, Dept. of Electrical Engineering, University of South Florida)
저널정보
한국인터넷방송통신학회 Journal of advanced smart convergence Journal of advanced smart convergence 제1권 제1호
발행연도
2012.1
수록면
6 - 13 (8page)

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An improved algorithm for image quality assessment is presented. First a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input images. This filter has one user-defined parameter, whose value depends on the reference image. This way the algorithm can adapt to different scenarios. In the next step the average value of locally computed correlation coefficients between the two processed images is found. This criterion is closely related to the way in which human observer assesses image quality. Finally, image quality measure is computed as the average value of locally computed correlation coefficients, adjusted by the average correlation coefficient between the reference and error images. By this approach the proposed measure differentiates between the random and signal dependant distortions, which have different effects on human observer. Performance of the proposed quality measure is illustrated by examples involving images with different types of degradation.

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