Choice of threshold of the Huber-Markov prior in MAP-based video resolution enhancement

The MAP (maximum a posteriori) -based resolution enhancement technique with Huber-Markov random field (HMRF) as the image prior has been proposed in the literature, and better preserves image discontinuities when compared with a Gaussian prior model. The reconstruction relies on the choice of Huber function parameter, or threshold T. There is no explicit selection of T in the previous studies. In this paper, we propose a method for choosing the threshold of the HMRF image prior in MAP based resolution enhancement. The method is based on the fact that the threshold T of the Huber function in the HMRF image priors is physically the trade-off between high-frequency components and low-frequency components for imagery data. High-pass filtering using the discrete Laplacian kernel along with the Huber function is used as the smoothness measure. When the high-passed value is less than T, the measure is a parabola function, while when the value is larger than T, the smoothness measure becomes a linear function. We hence define two different sets and derive the MAP estimator as a function of T Experimental results are presented and conclusions are drawn.