Reconstruction of multiview images taken with non-regular sampling sensors

Increasing spatial image resolution is a widely discussed area in the field of image processing. In this paper, we present an efficient reconstruction approach for high-resolution images, taken with irregularly shielded low-resolution sensors in a multiview setup. The approach is based on the sparsity assumption, meaning that natural images can be efficiently represented in a transform-domain using only few coefficients. Utilizing information from adjacent cameras results in a better reconstruction quality for the central high-resolution view. Since neighboring camera perspectives might differ in illumination, the information from adjacent views has to be adapted to the view to be reconstructed. The simulation results show that a proper incorporation of information from neighboring views leads to a PSNR gain of up to 2.20 dB compared to a state-of-the-art singleview reconstruction approach.