Tilting Mode Sampling Image Restoration Based on Hybrid Adaptation of Reciprocal Cell-HMT Model

Traditional methods of image restoration tend to only think of the influence of noise and blur on image quality during the image acquisition process, alias is ignored.Due to the anisotropic characteristics of modulation transfer function of the tilting mode sampling system, the adaptation of the reciprocal cell can confine the shape of the unit with little alias and noise.In this paper, the Bayesian method and wavelet domain Hidden Markov Tree model are treated as prior models, a method combining adaptation of the reciprocal cell with HMT model is proposed for tilting mode sampling image restoration.The experimental results show that the method can effectively improve the image resolution, and is better than the commonly used image restoration methods.