Date of Publication :29th March 2024

Abstract: Underwater imaging is an essential tool in various domains, including marine biology, underwater archaeology, and offshore inspection. However, underwater images often suffer from poor visibility, color distortion, and low contrast due to the absorption and scattering of light in water. To address these challenges, this paper proposes a novel underwater image enhancement method that combines Contrast Limited Adaptive Histogram Equalization (CLAHE) and the Dark Channel Prior (DCP) algorithm. The Contrast Limited Adaptive Histogram Equalization (CLAHE) technique enhances local contrast and mitigate the effects of uneven illumination, commonly encountered in underwater scenes. CLAHE adaptively equalizes the histogram of small image regions, preserving details and enhancing the overall image quality. The Dark Channel Prior (DCP) algorithm, leverages the statistical property of outdoor haze-free images to remove the inherent haze in underwater images. By effectively subtracting the underwater haze, DCP restores the image's original color and contrast. In our proposed method, CLAHE and DCP are integrated to harness their complementary strengths. First, CLAHE is applied to the underwater image to enhance local contrast and reduce uneven illumination effects. Then, the Dark Channel Prior is employed to estimate and remove the residual haze, further improving image clarity and color fidelity. The proposed method offers a valuable tool for improving the visibility and quality of underwater images, facilitating better understanding in various underwater applications.

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