A multiplicative weighted L2-norm total variation regularization for deblurring algorithms

In this paper a new deblurring algorithms for a special deconvolution problem, where a parameter describes the degree of blurring, is considered. The algorithm is based on a Conjugate Gradient technique and used the recently developed weighted l(2)(Omega)-norm Total Variation regularizer to obtain a reasonable solution. In order to avoid the necessity of determining the appropriate regularization parameter for this TV regularizer, this TV regularizer is included as a multiplicative constraint. In this way the appropriate regularization parameter is determined by the deblurring process itself. Numerical test shows that the proposed algorithm works very effective.