Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image information and visual quality
IEEE Transactions on Image Processing
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
IEEE Transactions on Image Processing
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The Structural SIMilarity (SSIM) index is an objective metric that gives relatively accurate similarity prediction scores with reasonable complexity. In this paper, an excellent trade-off between accuracy and complexity is presented in the form of a wavelet structural similarity index (WSSI), which is more accurate and less complex than the spatial SSIM index. Like the spatial SSIM index, the WSSI has the feature of boundedness. It computes an edge structural similarity map and an approximation structural similarity map to obtain the final similarity score. A contrast map is introduced in the wavelet domain for pooling structural similarity maps. Experimental results show that the low-complexity WSSI gives a correlation coefficient of 0.9548 between objective and subjective scores, and competes with visual information fidelity (VIF) performance.