Underwater Image Enhancement Based on Improved Histogram Matching and Adaptive Equalization

To improve the color of underwater imaging more effectively, and enhance the contrast and clarity of images, an underwater image enhancement method based on improved histogram matching and adaptive equalization is proposed. Each channel image is subjected to histogram matching using the histogram of the channel image with the largest pixel mean as the benchmark to correct the color deviation of the underwater image; taking full advantage of the independence of the color and lightness components in the HSI color space, this method performs an adaptive local histogram equalization on the lightness component, further improving the contrast and clarity of the image. Subjective and objective experimental data show that compared with some existing methods, the proposed method achieves better visual effects on underwater images after enhancement, with higher information entropy, an average gradient, UIQM, and SSIM. Therefore, the proposed method has a better enhancement effect on underwater images.