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Abstract
The total variation (TV) image denoising model has been investigated in this study. The traditional TV model was reviewed and a new algorithm of the total variation model was proposed. The balance point of the image feature and image noise was considered to set the first stop criterion in the imaging processing iteration step. On the basis of the first stop criterion, the second stop criterion took the variation of image noise into account. Comparing two stop criterions proposed in this paper, the first stop criterion has low computational complexity, while the second stop criterion can locate the optimal iteration step and obtains good image denoising results. A series of experimental results are used to test the model and it is shown that the new model with the second stop criterion can accurately locate the iteration step of optimal peak signal-to-noise ratio (PSNR), while the new model with the first stop criterion can perform rapid denoising, especially for images with high level of noise.