MATLAB Implementation of Structural Similarity Index Function
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This section introduces a classic digital image quality assessment method known as the Structural Similarity Index Function. The SSIM function serves as a widely-used approach for measuring image quality by comparing structural and content similarities between images. This method enables comprehensive image quality analysis and provides more accurate evaluation results. The MATLAB implementation typically involves calculating luminance, contrast, and structure comparison components using functions like imgaussfilt for Gaussian filtering and mean2 for local statistics computation. The algorithm follows the mathematical formulation: SSIM(x,y) = [l(x,y)]^α · [c(x,y)]^β · [s(x,y)]^γ, where luminance, contrast and structure comparisons are weighted through adjustable parameters. Key implementation steps include window-based local processing, dynamic range normalization, and default parameter settings (α=β=γ=1, C1=0.01, C2=0.03) for stability.
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