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A Fast and Flexible Algorithm for Total Variation Regularization

Brendt Wohlberg

Total Variation (TV) regularization has been successfully applied to a wide variety of image restoration problems, including denoising, deconvolution, and tomography. A modified form of this approach has recently been found to provide superior performance in denoising of images with speckle noise and other applications. Efficient algorithms for solving the modified problem have, until recently, not been available. We have developed a very flexible method for solving a general form of the TV functional, competitive with the state of the art for the denoising problem, and capable of solving more general inverse problems, which is not possible using most competing methods.