Image restoration is actually complicated because of the spatial-domain overlapping of noise and blur which can cause image degradation. In order to simplify restoration and improve recovery quality, it is proposed that the original double degradation model being translated into a single degradation model which contains only dynamic noise by utilizing proximal operator. Based on traditional total variation model, the seperable version is proposed by introducing low-dimension differential projection. The dynamic noise can be removed through first-order gradient descent algorithm. The results show that this method is applicable to a variety of degradation models, which effectively remove noise and blur with edges and details kept, even in a strong degradation environment. This makes degraded image recover to ideal status.