Share Email Print

Proceedings Paper

MUM (Merge Using Moments) segmentation for SAR images
Author(s): Rod Cook; Ian McConnell; Christopher John Oliver; Edward Welbourne
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 21 December 1994
PDF: 12 pages
Proc. SPIE 2316, SAR Data Processing for Remote Sensing, (21 December 1994); doi: 10.1117/12.197529
Show Author Affiliations
Rod Cook, N.A. Software (United Kingdom)
Ian McConnell, N.A. Software (United Kingdom)
Christopher John Oliver, Defence Research Agency Malvern (United Kingdom)
Edward Welbourne, N.A. Software (United Kingdom)

Published in SPIE Proceedings Vol. 2316:
SAR Data Processing for Remote Sensing
Giorgio Franceschetti, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?