Abstract
Due to the absorption and scattering effect on light when traveling in water, underwater images exhibit serious weakening such as color deviation, low contrast, and blurry details. Traditional algorithms have certain limitations in the case of these images with varying degrees of fuzziness and color deviation. To address these problems, a new approach for single underwater image enhancement based on fusion technology was proposed in this article. First, the original image is preprocessed by the white balance algorithm and dark channel prior dehazing technologies, respectively; then two input images were obtained by color correction and contrast enhancement; and finally, the enhanced image was obtained by utilizing the multiscale fusion strategy which is based on the weighted maps constructed by combining the features of global contrast, local contrast, saliency, and exposedness. Qualitative results revealed that the proposed approach significantly removed haze, corrected color deviation, and preserved image naturalness. For quantitative results, the test with 400 underwater images showed that the proposed approach produced a lower average value of mean square error and a higher average value of peak signal-to-noise ratio than the compared method. Moreover, the enhanced results obtain the highest average value in terms of underwater image quality measures among the comparable methods, illustrating that our approach achieves superior performance on different levels of distorted and hazy images.
Highlights
In recent years, underwater images have been widely used in marine energy exploration, marine environment protection, marine military, and other fields.[1]
Four existing excellent underwater images processing methods are utilized to compare with the proposed approach, that is, contrast limited adaptive histogram equalization (CLAHE),[10] dark channel prior (DCP),[4] multiscale Retinex with color restoration (MSRCR),[12] and fusion-based approach (FB).[13]
Most of the images used for the experiments come from FB data set,[13] U45 data set,[19] and real-world underwater image enhancement (RUIE) data set.[20]
Summary
Underwater images have been widely used in marine energy exploration, marine environment protection, marine military, and other fields.[1]. The brightness of the color-corrected image is inversely proportional to the value of l2 This WB method derives the first input of the fusion process from the original underwater image efficiently. The DCP dehazing algorithm derives the second input of the fusion process from the color-corrected version It takes into account the underwater image degradation process; it can effectively eliminate the partial reddish effect and enhance the contrast of the underwater image. The specific methods are shown in reference.[13] Multiscale fusion calculation is as follows lðx; Gl fW yÞgLlfI yÞg ð7Þ where l denotes the number of the pyramid levels (l 1⁄4 5), LfIg represents the Laplacian version of the input I, and GfW g denotes the Gaussian version of the normalized weight map W. The recovered output is obtained by adding the fusion contributions of all inputs
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