Implementation of Multi-Scale Retinex (MSR) for Foggy Image Processing

Implementation of the Multi-Scale Edge-Preserving Enhancement (MSR) algorithm within the Retinex framework, primarily applied for foggy image processing. This algorithm effectively enhances the quality of foggy images by improving clarity and achieving balanced brightness. By processing images at different scales using Gaussian filters with varying standard deviations, the MSR algorithm preserves edge information while simultaneously boosting contrast and detail visibility. Key implementation steps include: 1) Converting the input image to logarithmic domain for illumination-reflectance separation, 2) Applying Gaussian filtering at multiple scales (typically three scales: fine, medium, and coarse) to estimate illumination components, 3) Combining weighted results from different scales to maintain edge integrity while suppressing halo artifacts. The algorithm's multi-scale approach enables natural-looking fog removal by adaptively handling both global illumination variations and local details. Consequently, applying MSR produces foggy images with more realistic appearances and significantly improved processing outcomes, making it particularly suitable for computer vision applications in adverse weather conditions.