I. Introduction
Remote sensing is the process of obtaining information about targeted objects or areas by measuring its reflected and emitted radiation from a distance. Remote sensing imaging can cover larger areas than other methods of telemetry data acquisition but it has low spatial resolution and very low in relation to the dimension of the sensed object. Higher resolution remote sensing images can be obtained by using better sensing devices, but it cost more. An effective way to increase image spatial resolution at lower cost is by using algorithm based approach, known as super-resolution (SR). SR in remote sensing applications is important because it can assist the visual interpretation of images in remote sensing application such as surveillance, target detection, agriculture, land use mapping, meteorology, etc.