Detecting areas of change in multiple snapshot images of a ground area called change detection is important in a variety of surveillance applications used by the Air Force and Department of Defense. For many such applications, images are constructed using Synthetic Aperture Radar SAR. SAR collects information about a scene by repeatedly collecting the response from pulses transmitted toward an area of interest. A Backprojection algorithm is used to construct high quality 2-dimensional images from SAR data. The focus of this project is the development of novel sequential and parallel algorithms for change detection using SAR imagery that utilize modern architectures and minimize energy. This enables real-time change detection on an airborne device. When backprojection image frames are used for change detection, the computational burden can be mitigated by rendering areas of low activity in low resolution called multiresolution processing. In this project, we extensively utilized this feature and developed novel change detection algorithms for multiresolution SAR.