Minimum Description Length segmentation adapted to different image sensors

Philippe Refregier; Frederic Galland; Pascal Martin; Guillaume Delyon; Nicolas Bertaux; Francois Goudail

doi:10.1117/12.572468

30 November 2004 Minimum Description Length segmentation adapted to different image sensors

Philippe Refregier, Frederic Galland, Pascal Martin, Guillaume Delyon, Nicolas Bertaux, Francois Goudail

Proceedings Volume 5611, Unmanned/Unattended Sensors and Sensor Networks; (2004) https://doi.org/10.1117/12.572468
Event: European Symposium on Optics and Photonics for Defence and Security, 2004, London, United Kingdom

Abstract

Determining the shape of one or several objects in an image is a fundamental task for many imaging systems. We propose here a general review of new techniques based on the information theory principles, which allows one to determine segmentation techniques without parameter to be tuned by the user. These techniques are quite general since they include, polygonal and spline parametric shape descriptions, level set models of contour and homogeneous partition of images. This approach can take into account the physical nature of the grey level fluctuations and is thus adapted to different new imaging systems. Furthermore, it can lead to fast algorithms (from a few hundred of ms to a few seconds depending on the complexity of the task to perform on 256 x 256 pixel images).

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Philippe Refregier, Frederic Galland, Pascal Martin, Guillaume Delyon, Nicolas Bertaux, and Francois Goudail "Minimum Description Length segmentation adapted to different image sensors", Proc. SPIE 5611, Unmanned/Unattended Sensors and Sensor Networks, (30 November 2004); https://doi.org/10.1117/12.572468

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KEYWORDS

Image segmentation

Image processing algorithms and systems

Synthetic aperture radar

Image sensors

Statistical analysis

Image processing

Imaging systems

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