Based on original nonnegativity and support constrains recursive inverse filtering (NAS-RIF) algorithm

an improved algorithm is proposed in this paper. In order to control the trade-off between fidelity to the observed image and smoothness of the restored image and to prevent noise amplification

a newly cost function of the NAS-RIF algorithm can be obtained by adding space-adaptive terms and a regularization term. The space-adaptive terms can be calculated through the local properties of the observed image and the noise variance. An estimating method of noise variance is also proposed in this paper. This improved algorithm uses conjugate-gradient routine to calculate the optimal result. The experimental results show that the improved NAS-RIF algorithm provides a better restoration result.