Optical imaging technology is one of the main technology for underwater detection and recognition. However, the serious image noise occurred in the optical imaging and the signal to noise ratio of image decreased, due to water scattering and turbulence, background light interference and other factors. In this paper, an underwater visual image denoising algorithm based on total variation method is proposed to improve the signal-to-noise ratio of the underwater image at the same time keep the detail information of images. Based on the linear noise model of the image, the total variation model of the image is established and the partial differential equation of image problem is converted to optimization problems, which can be solved by gradient descent algorithm and finite difference algorithm. The method based on total variation was proposed to reduce the noise of underwater images compare with other traditional algorithms and verified by the simulation experiment and underwater experiment. Experimental verifications: after the image processing of the algorithm, the objective reference image quality evaluation index image peak signal-to-noise ratio (PSNR) was improved to more than 20 dB, and the score of no reference image quality evaluation index was improved by 4.8 times. The method can be applied to an underwater exploration and image enhancement for scatterer imaging applications.
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