Abstract and subjects
Total variation (TV) regularization has become a popular method for a wide variety of image restoration problems, including denoising and deconvolution. A number of authors have recently noted the advantages of replacing the standard l(2) data fidelity term with an l(1) norm. We propose a simple but very flexible method for solving a generalized TV functional that includes both the l(2)-TV and l(1)-TV problems as special cases. This method offers competitive computational performance for l(2)-TV and is comparable to or faster than any other l(1)-TV algorithms of which we are aware.