Under Water Image Contrast Enhancement

Enhancing underwater images is crucial in unveiling concealed aspects of the submerged realm, facilitating a more lucid depiction of aquatic environments, marine creatures, and archaeological locations. Enhancing underwater images has garnered considerable interest, given its relevance in marine engineering and aquatic robotics. In recent years, a multitude of algorithms have emerged for this purpose. However, these approaches are commonly evaluated using real-world underwater images. Suboptimal illumination conditions frequently afflict underwater image captures, obscuring vital visual details and compromising overall quality. This paper introduces technique for improving underwater image contrast enhance to improve the quality of the low light below-surface photos. The proposed method uses contrast enhancement principle to obtain an enhanced image with the original colors of the image preserved as much as possible, this is implemented by the compensation of all the three color channels by taking one color channel as reference. In this work, the color corrected image given as input is split into a, b and l channels where the intensity levels of the l channels are normalized. This contrast enhanced image is then processed using grey world hypothesis and the output is dehazed. The proposed efficient underwater image enhancement method that incorporates the locally adaptive contrast principles for effective color correction has been developed. The proposed approach has shown remarkable outcomes in elevating the quality of underwater images by striking a harmonious balance between color precision and contrast enhancement. This is reflected in its performance in terms of parameters such as Average gradient, Edge intensity, and the Patch Based Contrast. These results are a testament to the effectiveness of the method in enhancing underwater image quality. The proposed algorithm is developed by using MATLAB R2020a.