MATLAB Implementation of Retinex Image Enhancement Algorithm

This documentation presents a MATLAB implementation of the Retinex image enhancement technique. Retinex is an advanced algorithm designed to improve image quality by simulating the human visual system's perception mechanism, effectively enhancing image brightness and contrast. The core implementation involves separating the image into illumination and reflectance components using logarithmic operations and Gaussian filtering. Key MATLAB functions utilized include imgaussfilt() for multi-scale retinex processing and im2double() for intensity normalization. The algorithm effectively eliminates shadows and reflections from images, resulting in clearer and more vivid visual outputs. Through MATLAB programming, we can efficiently implement this technique using matrix operations and convolution functions, making it applicable to various image processing tasks. By adjusting critical parameters such as Gaussian kernel sizes and scale weights in the retinex implementation, users can optimize enhancement results according to specific requirements. The MATLAB implementation typically involves creating custom functions for single-scale retinex (SSR) or multi-scale retinex (MSR) with color restoration capabilities. This approach provides a straightforward yet powerful method for enhancing visual image quality while meeting diverse image processing needs through programmable parameter tuning and algorithm customization.