Underwater Image Enhancement based on Adaptive Color Correction with Improved Multi-Scale Fusion

Due to the selective absorption and scattering effects of water on light, underwater images generally face the challenges of color distortion, contrast degradation, and detail blurring, and in order to cope with these challenges, this paper proposes a multi-scale fusion-based underwater image enhancement method aimed at improving the visual quality of underwater images. Firstly, image blurring is mitigated by defogging, and adaptive color correction is introduced to differentiate underwater images into color-bias ed-free images and different types of color-biased images and then compensate the corresponding channels. Subsequently, CLAHE is applied to enhance the brightness and contrast and a fast bootstrap filter is applied to the brightness component for smoothing. Simultaneously, Laplace contrast weights are calculated and along with various other weights including saturation, local contrast, saliency and exposure, multilevel image fusion is achieved by pyramid decomposition and reconstruction technique. The experimental results show that the fused image has significant improvement in color, clarity and contrast, providing an effective solution for underwater image processing.