In order to better recovery texture details of images, avoid the difficulty of selecting the regularization parameters when solving the image deblurring model, a novel non-blind image deblurring method by using fractional order TV (FOTV) and adaptive estimation of two regularization parameters was proposed in this paper. First, after analyzing the amplitude-frequency response of FOTV, different fractional orders of FOTV were set to the smooth (low-frequency) part and texture (high-frequency) part of the desired image, respectively, and a model of image non-blind reconstruction was modeled. Second, to effectively solve the reconstruction model and adaptively update two regularization parameters, the alternating direction multiplier method (ADMM) was used to separate the originally complex problem with two regularization parameters into two easy sub-problems. Each sub-problem has only one regularization parameter. Finally, according to the discrepancy principle, the two regularization parameters were adaptively updated and two sub-problems were solved. To test the effect of deblurring with four blurring kernels, the proposed algorithm has been applied to multiple images with smooth, edge and texture details. Compared with four traditional deblurring algorithms, the experimental results showed that the proposed algorithm can adaptively update two regularization parameters and has better deblurring performance for images with moderate texture details.
