Orthogonal projection algorithm for first and second order total variation denoising

Idriss El Mourabit, Mohammed El-Rhabi, Abdelilah Hakim


The denoising problem is the process of removing the noise from a degraded image. As we know, the Rodin Osher Fatemi (ROF) denoising model based on total variation is a robust approach for solving the ill-posed problem. To avoid the staircasing effects caused by the first order total variation, the second order one is proposed. In this work, we present an orthogonal projection algorithm for solving the ROF model with first and second order total variation. The efficiency and robustness against noise of the proposed model are illustrated and compared with the classical methods through numerical simulations.

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