Jacqueline Le Moigne

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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, find the (affine) transformation that transforms one point set so that its distance from(More)
The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow(More)
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 running times by storing the points in a(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 gecgraphic region, but the exact alignment between the images io(More)
Recent advances in sensor technology have led to the development of hyperspectral sensors capable of collecting remote sensing imagery at several hundred bands over the spectrum. While these developments hold great promise for Earth science, they create new processing challenges. Therefore, processing hyperspectral data using new efficient techniques is a(More)
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)