MUM (Merge Using Moments) segmentation for SAR images

Rod Cook; Ian McConnell; Christopher John Oliver; Edward Welbourne

doi:10.1117/12.197529

21 December 1994 MUM (Merge Using Moments) segmentation for SAR images

Rod Cook, Ian McConnell, Christopher John Oliver, Edward Welbourne

Proceedings Volume 2316, SAR Data Processing for Remote Sensing; (1994) https://doi.org/10.1117/12.197529
Event: Satellite Remote Sensing, 1994, Rome, Italy

Abstract

In Synthetic Aperture Radar (SAR) and other systems employing coherent illumination to form high-resolution images, the resulting image is generally corrupted by a form of multiplicative noise, known as coherent speckle, with a signal-to-noise ration of unity. This severe form of noise presents singular problems for image processing software of all kinds. This paper describes a segmentation scheme, Merge Using Moments (MUM), for image corrupted by coherent speckle. The image is initially massively over-segmented. A scheme based on examination of the statistical properties (moments) of adjoining regions is employed to improve an over-fine segmentation by merging regions to produce a coarser segmentation. This scheme is employed iteratively until no remaining merge appears valid, at which time a good segmentation is obtained. Segmentation using μm on SAR imagery are given and the results compared to other segmentation schemes. The results of using it on typical SAR images illustrate its potential.

Citation Download Citation

Rod Cook, Ian McConnell, Christopher John Oliver, and Edward Welbourne "MUM (Merge Using Moments) segmentation for SAR images", Proc. SPIE 2316, SAR Data Processing for Remote Sensing, (21 December 1994); https://doi.org/10.1117/12.197529

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