Bayesian stereoscopic image resolution enhancement

Resolution enhancement for stereo imaging aims to use a pair of stereo images to reconstruct another pair of images with higher resolution. To tackle this problem, a Bayesian resolution enhancement approach is proposed in this paper. Since the prior image model is essential for solving the ill-posed numerical issues encountered in the image resolution enhancement, the proposed approach exploits a prior image model which considers both the spatial local smoothness constraint within each reconstructed high-resolution image and the disparity-compensated local smoothness constraint between the pair of reconstructed high-resolution images. Then the proposed prior image model is further incorporated into a Bayesian inference formulation to perform stochastic image reconstruction. Experiments are conducted to demonstrate the superior performance of the proposed approach.