Image Defogging with Retinex Algorithms

In image processing, the Retinex algorithm stands as a classical approach for image enhancement. It operates by separating an image into its fundamental components: illumination and reflectance. By adjusting the intensity of the reflectance component, this algorithm enhances image brightness and contrast. The Single-Scale Retinex Algorithm (SSR) represents a variant that processes images using only one scale parameter, which may limit its effectiveness in handling images with diverse lighting conditions. To address this limitation, the Multi-Scale Retinex Algorithm (MSR) was developed, employing multiple scale parameters and combining their outputs to achieve superior results. For further enhancement, the Multi-Scale Retinex with Color Restoration Algorithm (MSRCR) incorporates color information considerations, applying color compensation during the enhancement process to deliver more natural-looking results. From an implementation perspective, these algorithms typically involve Gaussian filtering operations at different scales, logarithmic transformations to separate illumination and reflectance components, and weighted combinations of multiple scale outputs. The MSRCR algorithm additionally includes color restoration factors that maintain color fidelity while enhancing image clarity. Key functions in implementation would include Gaussian kernel generation, convolution operations for filtering, and color space transformations for optimal color processing.