Enhancing RGB retinal images is vital for retinopathy detection and monitoring, but issues like uneven intensity often degrade visual quality. This research introduces a digital diffraction-based method to improve uneven intensity and contrast while preserving color naturalness. Initially, the retinal image is converted to LCH color space, where intensity correction is applied to the L channel, treated as an optical field. A digital propagation with a specific kernel estimates the intensity pattern, which, when subtracted, yields a corrected L channel. Multi-image fusion with varied kernels then ensures uniform intensity. The same process corrects the C channel for color accuracy. Tested on 1 200 Messidor dataset images, this method surpasses Gamma correction and Retinex methods, enhancing contrast and uniformity by 3%-4% when combined with CLAHE. The improved contrast aids applications like retinopathy detection and blood vessel segmentation.