Image quality enhancement based on real-time deconvolution and super resolution
Yoan Marin, Abdelali Douiyek, Johel Mitéran, Julien Dubois, Barthélémy Heyrman, Dominique Ginhac · 2018
Despite the evolution of technologies, high-quality image acquisition systems design is a complex challenge. Indeed, during the image acquisition process, the recorded image does not fully represent the real visual scene. The recorded information could be partial due to dynamic range limitation and degraded due to distorsions of the acquisition system. Typically, these issues have several origins such as lens blur, or limited resolution of the image sensor. In this paper, we propose a full image enhancement system that includes lens blur correction based on a non-blind deconvolution followed by a spatial resolution enhancement based on a Super-Resolution technique. The lens correction has been software designed whereas the Super-Resolution has been both software and hardware (on an FPGA) implemented. The two processing steps have been validated using well-known image quality metrics, highlighting improvements of the quality of the resulting images.