Automatic Registration of INSAT-3D Daily Images Using Mutual Information and Stochastic Optimization Technique

Abstract

An automatic image registration approach is presented here can be used to register daily images of Indian geostationary satellite system INSAT-3D acquired every 30 min’ interval without use of any ground control points (GCPs). There is always a pressing need to register meteorological images that are acquired over earth from geostationary platforms every 15–30 min, covering almost one-third of the earth. Weather forecast activities include derivation of atmospheric motion vectors, which demand immediate processing of such images to a reasonable accuracy in terms of its relative location accuracy. Generally followed approaches make use of image navigation models and GCPs drawn from known landmarks in land ocean boundaries and correlate image features before estimating a transform to warp the current acquisition to a known geometry. However, the hierarchical (coarse to fine) approach explained here makes use of intensity based Mutual Information as a similarity measure from a population of pixels selected randomly and uses stochastic gradient descent optimizer to estimate an affine transform between registering image pair, delivers satisfactory results.