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Statistical Evaluation of Image Quality Measures

By Ismail Avcibas, İsmail Avcıbaş, Bulent Sankur and Khalid Sayood


In this work we categorize comprehensively image quality measures, extend measures defined for gray scale images to their multispectral case, and propose novel image quality measures. They are categorized into pixel difference-based, correlation-based, edge-based, spectral-based, context based and HVS-based (Human Visual System-based) measures. Furthermore we compare these measures statistically for still image compression applications. The statistical behavior of the measures and their sensitivity to coding artifacts are investigated via Analysis of Variance techniques. Their similarities or differences have been illustrated by plotting their Kohonen maps. Measures that give consistent scores across an image class and that are sensitive to coding artifacts are pointed out. It has been found that measures based on phase spectrum, on multiresolution distance or HVS filtered mean square error are computationally simple and are more responsive to coding artifacts

Year: 2002
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