Remote Sensing Image Registration Based On Particle Swarm Optimization And Mutual Information

Abstract

The image registration is an indispensable process in remote sensing image processing. The remote sensing registration data is the process of aligning one image to a second image of the same scene that is acquired at the same or at different times by the different or the same sensors. This paper proposes an optimization approach for remote sensing image registration. The approach is proposed for determining pairs of corresponding points between the images, the approach based on the implementation of particle swarm optimization (PSO) used as a function optimizer and mutual information (MI) is used as a similarity measure. The first, Landmarks were chosen manually and used thin plate spline (TPS) to provide a geometric representation for the relative locations of corresponding landmarks. Secondly, MI was used as a cost function to determine the degree of similarity between two images. Finally, PSO was used to improve the correspondence between the landmarks and to maximize MI function. Keywords Remote sensing, Image registration, Particle swarm optimization, Mutual information and image fusion.