Title: Remote Sensing Image Matching Using Contourlet-Based Key Points Descriptors and Convex Hull Regions
Year of Publication: 2015
Publisher: International Journal of Computer Systems (IJCS)
ISSN: 2394-1065
Series: Volume 2, Number 12
Authors: Ibrahim El rube, Omar El Khatib and Ahmed R. Salman


Ibrahim El rube, Omar El Khatib, Ahmed R. Salman, "Remote Sensing Image Matching Using Contourlet-Based Key Points Descriptors and Convex Hull Regions", International Journal of Computer Systems (IJCS), 2(12), pp: 546-551, December 2015. BibTeX

	author = {Ibrahim El rube, Omar El Khatib, Ahmed R. Salman},
	title = {Remote Sensing Image Matching Using Contourlet-Based Key Points Descriptors and Convex Hull Regions},
	journal = {International Journal of Computer Systems (IJCS)},
	year = {2015},
	volume = {2},
	number = {12},
	pages = {546-551},
	month = {December}


The rapid growth of the remote sensing image databases requires an efficient and effective algorithm for matching and retrieving these images. In this paper, a remote sensing image matching method using simple descriptors for Contourlet-based key points and convex hull regions algorithm is presented. The key points are extracted using the previously introduced Contourlet-based detector, then a simple descriptor is computed for each key point. Correspondences between the reference image and the sensed image are calculated in order to rectify the sensed image. Consequently, convex hull regions are created from Delaunay triangulation of the key points of the rectified image. The triangle regions are invariant to translation, rotation, scale and skew transformations. The robustness and the accuracy of the proposed algorithm are examined by the widely used remote sensing images. The experimental results show that the presented remote sensing image matching algorithm is robust and invariant to geometric transformations.


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Remote sensing images, image matching, image registration, Contourlet transform, geometric transformation.