Underwater Image Enhancement and Edge Preserving using GA

This Image enhancement (IE)methods present as a preprocessing step in object finding and credit in computer vision applications. The nature of underwater images is poor due to particular engendering assets of light in water. In this way, underwater image enhancement is important to increment visual quality. In this research, presented an underwater IE and Edge preserving using an optimized genetic algorithm (GA). Utilizing GA Optimization, it is performed through common trade of genetic material between parents. Offsprings are framed from parent qualities. Wellness of offsprings is assessed. The fittest people are permitted to breed as it were. In PC world, genetic material is supplanted by series of bits and normal choice supplanted by a fitness function. Matting of parents is represented by cross-over and mutation operations. The performance evaluation based on the peak signal noise ratio (PSNR) and entropy. The comparison of our proposed is on PSNR which shows better than previous methods (Base, CLAHE and Homomorphic Filtering (HF)). The experimental database contains underwater image, seawater image.