For the constraints validity problem of the Huber-Markov random field prior model in MAP super-resolution

an adaptive threshold HMRF model is proposed in this paper to make an adaptive choice of the threshold of the Huber edge penalty function. In iteration

by analyzing the relationship between the Huber penalty function and the distribution character of the image spatial gray level variation

statistical properties of the image spatial gray level variation is used as the basis for dynamically determining the threshold. Experimental results show that the proposed method can choose the threshold of Huber penalty function adaptively for images with different edge characteristics

restrain the noise

and preserve the edges details effectively.