Two-step super-resolution technique using bounded total variation and bisquare M-estimator under local illumination changes

In this paper, we present a super-resolution (SR) technique for images having arbitrarily-shaped local illumination changes. These variations tend to degrade the performance of the image registration, and hence impact the SR image reconstruction. Conventional SR techniques focus on enhancing the reconstruction step assuming aligned images. In this paper, we exploit our recent registration approach of images having illumination variations using a robust bisquare M-estimation. Then, we extend a bounded total variation-based approach for upsampling single frames to super-resolving multi-frames in order to reconstruct the unknown high-resolution (HR) frame. The proposed SR technique shows clear improvements over competing techniques in terms of objective metrics using simulated and real image pairs with illumination variations.