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In order to solve the problems of color distortion and blurring common in underwater images, this paper uses color channel compensation and grayscale equalization to correct color cast, and uses the total variation of the reweighted graph to estimate the fuzzy kernel to achieve image restoration. Based on the average gray value of the color channel, the color channel with serious information loss is compensated to reduce the deviation of the gray distribution between the color channels, and the gray distribution balance is further realized by segmented stretching. Combined with the reweighted graph total variation prior algorithm and the improved L-R unblinded restoration algorithm to restore the final image to remove blurring. Several sets of different data sets were selected to compare the proposed algorithm with several classical algorithms, and the evaluation results of subjective vision and three objective indicators were analyzed. The results show that the proposed algorithm can be applied to underwater image restoration, and the algorithm has good general applicability, which can effectively correct color cast, remove blur and improve image clarity.
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