Overlapping combined sparse total variation HFOGSTV denoising model based on fractional mixing order
Aiming at the problem of block-like artifacts in images caused by the staircase effect caused by total variation(TV)model,this paper proposes an overlapping combined sparse regular term denoising HFOGSTV model based on fractional mixing order.Considering that the overlapping combination of sparse regularization term and fractional differentiation can suppress global and local block artifacts,this paper introduces them into the TV model to better suppress the ladder effect.Furthermore,high-order differentiation is introduced to improve the denoising efficiency of the model,and an overlapping combined sparse regular term denoising HFOGSTV model based on fractional mixing order is constructed.The new model is decomposed into each subproblem by alternating direction multiplier ADMM method,and the appropriate parameters are selected.The experimental results show that compared with the NLM,TV,and HNHOTV-OGS models,the PSNR of the HFOGSTV model increases by 7.2%,5.3%,and 1.9%,respectively,and the SSIM increases by 6.6%,6.1%,and 3.4%,respectively,while the running time decreases by 89%,51%,and 45%,respectively.It not only effectively suppresses the staircase effect,but also has better denoising effect and greatly reduces the running time.
image denoisingoverlapping combination sparsefractional differentiationalternating direction multiplier algorithm
NETL
NSTL
万方数据
