Jacqueline Le Moigne

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Genetic algorithms (GAs) are known to be robust for search and optimization problems. Image registration can take advantage of the robustness of GAs in finding best transformation between two images, of the same location with slightly different orientation, produced by moving spaceborne remote sensing instruments. In this paper, we present 2-phase(More)
Image registration is the process by which we determine a transformation that provides the most accurate match between two images. The search for the matching transformation can be automated with the use of a suitable metric, but it can be very time-consuming and tedious. We introduce a registration algorithm that combines a simple yet powerful search(More)
One of the basic building blocks in any point-based registration scheme involves matching feature points that are extracted from a sensed image to their counterparts in a reference image. This leads to the fundamental problem of point matching: Given two sets of points, nd the (aane) transformation that transforms one point set so that its distance from the(More)
One of the basic building blocks in any point-based registration scheme involves matching feature points that are extracted from a sensed image to their counterparts in a reference image. This leads to the fundamental problem of point matching: Given two sets of points, find the (affine) transformation that transforms one point set so that its distance from(More)
Received () Revised () Communicated by () Clustering is central to many image processing and remote sensing applications. isodata is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to isodata clustering, which achieves better(More)
Given two images of roughly the same scene, image registration is the process of determining the transformation that most nearly maps one image to another. This problem is of particular interest in remote sensing applications, where it is known that two images correspond to roughly the same gec-graphic region, but the exact alignment between the images io(More)