Super-resolution/segmentation of 2D trabecular bone images by a Mumford-Shah approach and comparison to total variation

The analysis of trabecular bone micro structure from in-vivo CT images is still limited due to insufficient spatial resolution. The goal of this work is to address both the problem of increasing the resolution of the image and of the segmentation of the bone structure. To this aim, we investigate the joint super-resolution/segmentation problem by an approach based on the Mumford-Shah model. The validation of the method is performed on blurred, noisy and down-sampled images. A comparison of the reconstruction results with the Total Variation regularization is showed.