GCD based Blind Super-Resolution for Remote Sensing Applications

The importance of remote sensing imageries is growing day by day. Extraction of fine details of desired regions worth for further processing and decision making. Usually the data bases of remote sensing imageries are very huge that overburden the processor. Super-Resolution overcomes this problem and yields a high-quality output in less time consumption. This paper aims to give a brief idea about one of the approaches of super-resolution known as blind super-resolution reconstruction approach. In this approach, Greatest Common Divisor (GCD) algorithm is embedded into the blind reconstruction technique. The HR images obtained from this method is compared with the interpolated images. The results shows the efficacy of the proposed method. The paper tries to overcome the limitations of the super resolution approach and a conclusive discussion of the whole method has been discussed.