Parallel Processing based Image Enhancing Technique Implementation on Low Cost FPGA

Low-light image augmentation is crucial in many applications where visibility is regularly impeded by suboptimal lighting, such as autonomous driving, surveillance, and medical imaging. Traditional photo improvement methods, such as histogram equalization and contrast alteration, usually fail to preserve image authenticity while boosting visibility. This study presents a novel Retinex-based parallel processing method designed for FPGA implementation using MATLAB and Xilinx Vivado that enhances low-light photos in real time. The evaluation measures used to gauge performance include Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). The findings revealed that the PSNR was 16.34 dB and the SSIM was 0.868. This paper provides a detailed description of the architecture, design, and implementation of the system,which then moves on to performance analysis and discussion.