Joint Fusion and Blind Restoration For Multiple Image Scenarios With Missing Data

Abstract

Image fusion systems aim at transferring ‘interesting’ information from the input sensor images to the fused image. The common assumption for most fusion approaches is the existence of a high-quality reference image signal for all image parts in all input sensor images. In the case that there are common degraded areas in at least one of the input images, the fusion algorithms cannot improve the information provided there, but simply convey a combination of this degraded information to the output. The authors propose a combined spatial-domain method of fusion and restoration in order to identify these common degraded areas in the fused image and use a regularized restoration approach to enhance the content in these areas. The proposed approach was tested on both multi-focus and multi-modal image sets and produced interesting results.