关键词: 超分辨率重建, 贝叶斯最大后验概率估计, 基于学习, 人脸图像, 最速下降优化

Abstract: Propose an algorithm that learned a prior on the spatial distribution of the images gradient for frontal images of faces，and then incorporated such a prior into the Maximum a Posterior Estimate（MAPE） algorithm.To get a single global minimum，use a gradient descent algorithm.Experimental results demonstrate that the proposed method is effective in reconstructing the high-frequency components of the images.Furthermore，the method can convert a small number（2-3） of low-resolution images of a face into a single high-resolution image.

Key words: super-resolution, Maximum a Posterior Estimate（MAPE）, learning-based, faces image, gradient descent