Determination of optimum window size for SAR image co-registration with decomposition of auto-correlation

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Abstract:

Abstract

Interferometric synthetic aperture radar (InSAR) is a promising recent technique for the generation of digital elevation models and/or the measurement of ground surface deformations. In InSAR data processing, the first step is the image co-registration, achieved by using a set of tie points which are the conjugate image points on the master and slave images. Tie points are selected with the aim of finding the conjugate point automatically on the slave image for any given point on the master image, by the process known as image matching. To achieve reliable matching, a set of points within a window is used instead of a single point. The size of the window will affect the reliability of matching. Hitherto there have been no effective methods for the determination of optimum window size for this purpose. In practice, this parameter is determined by experience. In this paper, a pair of SAR images is used to test the effect of window size on the reliability of co-registration. An optimum window size is selected on the basis of the experimental results. The determination of optimum window size for tie point matching is then examined theoretically, leading to a proposal for an automated method based on the auto-correlation of the SAR images, which reflects the similarity between image pixels. The auto-correlation function is decomposed into waves of various frequencies by a wavelet transform. By a combined analysis of the variations of wave amplitudes with frequency, the optimum window size for tie point matching can be determined. A procedure based on the use of Daubechies wavelet db1 is proposed in detail. An optimum window size could be determined in this way for any pair of SAR images.

Keywords: InSAR; auto-correlation coefficient; co-registration; optimum window size; tie point matching; wavelet transform

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1477-9730.2007.00443.x

Affiliations: 1: ( ), Email: hkzouwb@yahoo.com 2: ( ), Email: lszlli@polyu.edu.hk 3: ( ) The Hong Kong Polytechnic University, Email: lsxlding@polyu.edu.hk

Publication date: September 1, 2007

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