Image Quality Assessment Algorithm (MS-SSIM)

The Multi-Scale Structural Similarity Index (MS-SSIM) is a widely used image quality assessment algorithm that requires a reference image to measure image distortion levels and fidelity. Based on the Structural Similarity Index (SSIM), MS-SSIM calculates quality scores by comparing structural and perceptual information between reference and test images across multiple scales using Gaussian pyramid decomposition. Key implementation steps include computing luminance, contrast, and structure comparisons at each scale, followed by weighted pooling across scales. This algorithm finds extensive applications in image processing fields such as image compression (evaluating codec performance), image enhancement (validating improvement algorithms), and image transmission (assessing network-induced distortions). By employing MS-SSIM, practitioners can achieve more accurate quality evaluations through its multi-resolution approach that better mimics human visual perception, thereby improving image processing outcomes and optimization effectiveness.