Automatic image registration framework for Remote Sensing Data using Harris Corner Detection and Random Sample Consensus (RANSAC) Model

Image registration is a fundamental image processing task to match and align physically two images which could have been imaged by different sensors, view angles or and at different times. It is necessary to have robust single frame image registration software especially an automated one. Automatic image registration framework overlays two images for geometric conformity aligning common features by establishing a transformation model using distinguishable feature points collected simultaneously in both the images in a completely un assisted manner. The critical steps in image registration are collection of feature points and estimating a spatial transformation especially when outliers are present besides feature matching and resampling the slave image to the master image geometry. In this paper, the details and merit of employing automatic Harris corner detection and building a transformation model using Random Sample Consensus (RANSAC) algorithm is brought out while registering a pair of AWIFS images from Indian Remote Sensing Satellite (IRS) platform. Potential available with this approach for performing large scale image registration tasks such as time series processing for change detection are highlighted.