An image super-resolution processing by using Hidden Markov Tree model to express the wavelet coefficients of the probability of structure is proposed. According to the properties of multiscale wavelet coefficients

the persistency and the exponential decay

wavelet coefficients of the image are modeled as Hidden Markov Tree model. Wavelet-domain HMT model considers the statistical properties of wavelet coefficients.The image interpolation is formulated as a constrained optimization problem. The high-resolution interpolated image which is able to maintain the original image information in the rich high-frequency is obtained. Experiment results show that the algorithm improves the traditional sawtooth effect and smoothing effect caused by interpolation. The PSNR and visual effects of interpolated image are improved obviously.