Fast variational algorithm for clutter removal through pyramidal domain decomposition

Lenny I. Rudin; Frederick Nordby; Georges Koepfler; Jean-Michel Morel

doi:10.1117/12.167536

1 March 1994 Fast variational algorithm for clutter removal through pyramidal domain decomposition

Lenny I. Rudin, Frederick Nordby, Georges Koepfler, Jean-Michel Morel

Proceedings Volume 2037, Chaos/Nonlinear Dynamics: Methods and Commercialization; (1994) https://doi.org/10.1117/12.167536
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

Abstract

Recent work has proven the feasibility and utility of 2-Normal segmentation as an image analysis tool. This technique, and the algorithm on which it is based, have shown dramatic and promising results for a number of image processing problems, such as clutter suppression, texture segmentation, motion analysis and object tracking. These capacities will be useful for clutter suppression, target location and classification, platform motion compensation, target tracking, vehicle guidance, battlefield mapping and target damage assessment. These and all applications of 2-Normal segmentation could easily employ and integrate multi-sensor data and /or multi-scale image preprocessing for analysis in two dimensions, three dimensions, or time sequence.

Citation Download Citation

Lenny I. Rudin, Frederick Nordby, Georges Koepfler, and Jean-Michel Morel "Fast variational algorithm for clutter removal through pyramidal domain decomposition", Proc. SPIE 2037, Chaos/Nonlinear Dynamics: Methods and Commercialization, (1 March 1994); https://doi.org/10.1117/12.167536

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