Motion-Based Blind Super-Resolution Approach to Overcome Spatial Limitation of Camera Sensor Network

Camera sensor network (CSN) is widely used in many new applications. But low quality images or videos obtained by cheap surveillance cameras are a bottleneck for the development of CSN. A new motion-based blind super-resolution algorithm is proposed to improve the resolution of acquired image. In this method, improved projection transformation is adopted to estimate relative motion of the low-resolution (LR) images and do motion compensation. Then a universal projection function is created and iterates to reconstruct high-resolution (HR) images from these shifted LR images with blur and noise under the condition that any parameters of the degradation model are unknown. The experiment shows that whether evaluate from subjective or objective way the method is robust and effective. The drawback is that noise are still exists and slightly enlarged in somewhere.