Learning to solve TV regularised problems with unrolled algorithms
Learning to solve TV regularised problems with unrolled algorithms
Total Variation (TV) is a popular regularization strategy that promotes piece-wise constant signals by constraining the l1-norm of the first order derivative of the estimated signal. The resulting optimization problem is usually solved using iterative algorithms such as proximal gradient descent, primal-dual algorithms or ADMM. However, such methods can require …