Deep Seabed Image Enhancement Algorithm for Manned Submersible Acquisition

Objective: Due to the problems of light propagation underwater, such as scattering and absorption, which leads to low contrast, color distortion and blurring of details in the images obtained underwater, this phenomenon is more serious in the deep sea, and most undersea map images collected by manned submersibles during deep-sea exploration exhibit these issues. To address these problems, an underwater image fusion enhancement algorithm based on color correction and image sharpening is proposed for image enhancement and restoration. Methods: The automatic color enhancement algorithm is used to correct and enhance the color of the underwater image. Subsequently, the RGB three channels are corrected by gamma filtering. The RGB space is then converted to the Lab space, and the L channel is processed by the Contrast Limited Adaptive Histogram Equalization algorithm to enhance the luminance. At the same time, the color-corrected image is image-sharpened by using unsharpened mask algorithms. Finally, image fusion is performed by using the algorithm based on the fusion of guided filters. Results: The experimental results on several underwater images under different scenarios show that the enhancement effect achieved by this algorithm is better than the comparison algorithm. In the subjective aspect, the color and details of the images are better balanced and enhanced. In the objective aspect, quantitative evaluations are carried out in three aspects: Information entropy (IE), underwater image quality measure (UIQM), and underwater color image quality evaluation (UCIQE), in which the IE is quantitatively evaluated. Regarding the UCIQE, the proposed algorithm has a better effect than other algorithms in terms of IE, UIQM, and UCIQE. Specifically, compared to the original image, the proposed algorithm shows improvements of 33.4%, 1.45 times, and 54.4% or more in mean value. Conclusion: The results show that the algorithm has good results in image processing for underwater environments, with enhancement and restoration of images acquired through manned submersibles.