| Citation: | BEN Y Y，TANG R，DAI P A，et al. Image enhancement algorithm for underwater vision based on weighted fusion[J]. Journal of Beijing University of Aeronautics and Astronautics，2024，50（5）：1438-1445 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0540
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Aiming at the problem of poor feature extraction and feature matching in the underwater visual simultaneous localization and mapping (SLAM) front end, an image-enhanced algorithm based on weighted fusion is proposed for the underwater visual SLAM front end. Specifically, the algorithm is based on the fusion of two images: the second image is a white balance of gray world based on color judgment and color compensation, and the first image is an underwater image from brightness enhancement based on adaptive gamma correction and dynamic range expansion. Furthermore, the saliency weight and saturation weight of the two images are calculated, and the input images are linearly weighted and fused to obtain the final enhanced image.The system is tested using an open-source dataset from the University of South Carolina, and the improved underwater image quality is assessed using the techniques of underwater color image quality evaluation (UCIQE) and underwater image quality measurement (UIQM). Consequently, the results show that the processed image has the characteristics of high quality and a large number of extracted feature points, which can significantly improve the effect of front end feature extraction and feature matching of underwater visual SLAM.
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