Designing of image enhancement technique for contrast and color improvement based on haze removal of underwater images

This work presents and analyses a revolutionary quality upgrade of an underwater image by haze removal and colour contrast enhancement utilizing a multi-image fusion based on fuzzy logic technique. Haze can lower vision and make extracting usable information from underwater photos challenging, which often degrades the images. Haze removal can enhance the visual quality of the photos and make additional analysis easier. Thus, it is recognized as a crucial and challenging task in the field of underwater image processing. In the presented approach first, white balancing and contrast enhancement is achieved parallelly using the Contrast Limited Adaptive histogram equalization (CLAHE) technique to generate two inputs from the given-colored image for further weight mapping and fusion. Weight mapping of Luminance Chromatic and Saliency components of the contrast-enhanced image and white balanced is achieved separately. In the second step fusion of all six components is done using Gaussian and Laplacian pyramids to produce high-quality haze-free underwater images. The success of our method in enhancing the contrast, color, and overall visual quality of underwater photos is shown by the experimental findings.