24 January 2012 Reduced-reference image quality assessment based on statistics of edge patterns
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Abstract
Recently, research of Objective Image Quality Assessment (IQA) has gained much attention due to its wide application prospect. Among them, the Reduced-Reference (RR) methods estimate perceptual quality of distorted images with partial information from the reference images. This paper proposes a novel universal RR-IQA metric based on the statistics of edge patterns. Firstly, the binary edge maps of the reference and distorted images are created by the LOG operator and zero-crossing detection. Based on them, 15 groups of typical edge patterns are extracted and then their statistical distributions are calculated respectively for the reference and distortion images. The proposed RR-IQA metric is achieved by computing the L-1 Minkowski distance between those two distributions. We have evaluated this metric on six publicly accessible subjective IQA databases. Experiments shows that the proposed metric featured with typical edge patterns outperform other methods in terms of data volume, accuracy and consistency with human perception. In a way, our work provides a new view to the IQA metric design.
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Yuting Chen, Yuting Chen, Wufeng Xue, Wufeng Xue, Xuanqin Mou, Xuanqin Mou, } "Reduced-reference image quality assessment based on statistics of edge patterns", Proc. SPIE 8299, Digital Photography VIII, 82990C (24 January 2012); doi: 10.1117/12.907973; https://doi.org/10.1117/12.907973
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