| Abstract: |
| Incorporating appropriate geometric priors into a variational denoising model has shown superiority in noise elimination while preserving important geometric features of the image, such as contrasts, corners, and edges. In this paper, we propose an effective variational model that utilizes the second fundamental form as the regularizer for multiplicative noise removal. |
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