Terrain feature identification by modeling radar image statistics

A G  Bors; E R  Hancock; R C  Wilson

Terrain feature identification by modeling radar image statistics

Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper we propose a new statistical model for SAR images. According to this model, the SAR image amplitude follows a product of Rayleigh and Bessel functions. We derive the maximum likelihood feature detector for extracting terrain features from Synthetic Aperture Radar (SAR) images. The terrain features are classified as ridges and ravines according to their statistical properties and surrounding neighborhood. These salient features are used as constraints for estimating the SAR terrain surface.

Original language	English
Pages (from-to)	721-724
Number of pages	4
Journal	2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL I, PROCEEDINGS
Publication status	Published - 2000

Cite this

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title = "Terrain feature identification by modeling radar image statistics",

abstract = "In this paper we propose a new statistical model for SAR images. According to this model, the SAR image amplitude follows a product of Rayleigh and Bessel functions. We derive the maximum likelihood feature detector for extracting terrain features from Synthetic Aperture Radar (SAR) images. The terrain features are classified as ridges and ravines according to their statistical properties and surrounding neighborhood. These salient features are used as constraints for estimating the SAR terrain surface.",

author = "Bors, {A G} and Hancock, {E R} and Wilson, {R C}",

year = "2000",

language = "English",

pages = "721--724",

journal = "2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL I, PROCEEDINGS",

issn = "1522-4880",

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TY - JOUR

T1 - Terrain feature identification by modeling radar image statistics

AU - Bors, A G

AU - Hancock, E R

AU - Wilson, R C

PY - 2000

Y1 - 2000

N2 - In this paper we propose a new statistical model for SAR images. According to this model, the SAR image amplitude follows a product of Rayleigh and Bessel functions. We derive the maximum likelihood feature detector for extracting terrain features from Synthetic Aperture Radar (SAR) images. The terrain features are classified as ridges and ravines according to their statistical properties and surrounding neighborhood. These salient features are used as constraints for estimating the SAR terrain surface.

AB - In this paper we propose a new statistical model for SAR images. According to this model, the SAR image amplitude follows a product of Rayleigh and Bessel functions. We derive the maximum likelihood feature detector for extracting terrain features from Synthetic Aperture Radar (SAR) images. The terrain features are classified as ridges and ravines according to their statistical properties and surrounding neighborhood. These salient features are used as constraints for estimating the SAR terrain surface.

M3 - Article

SP - 721

EP - 724

JO - 2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL I, PROCEEDINGS

JF - 2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL I, PROCEEDINGS

SN - 1522-4880

ER -