Iterative Refinement of Transformation Parameters for Image Registration
Image registration is an important process in high-level image
interpretation systems developed for civilian and defense
applications. Registration is carried out in two phases: namely feature extraction and feature correspondence. The
basic building block of feature based image registration
scheme involves matching feature points that are extracted
from a sensed image to their counter parts in the reference
image. Features may be control points, corners, junctions or
interest points. The objective of this study is to develop a
methodology for iterative convergence of transformation
parameters automatically between two successive pairs of
aerial or satellite images. In this paper we propose an iterative
image registration approach to compute accurate and stable
transformation parameters that would handle image sequences
acquired under varying environmental conditions. The
iterative registration procedure was initially tested using
satellite images with known transformation parameters like
translation, rotation, scaling and the same method is further
tested with images obtained from aerial platform.
Keywords: Image registration, Corner Detector,
Homography, Correlation
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