## Scene estimation from speckled synthetic aperture radar imagery: Markov-random-field approach

JOSA A, Vol. 23, Issue 6, pp. 1269-1281 (2006)

http://dx.doi.org/10.1364/JOSAA.23.001269

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### Abstract

A novel Markov-random-field model for speckled synthetic aperture radar (SAR) imagery is derived according to the physical, spatial statistical properties of speckle noise in coherent imaging. A convex Gibbs energy function for speckled images is derived and utilized to perform speckle-compensating image estimation. The image estimation is formed by computing the conditional expectation of the noisy image at each pixel given its neighbors, which is further expressed in terms of the derived Gibbs energy function. The efficacy of the proposed technique, in terms of reducing speckle noise while preserving spatial resolution, is studied by using both real and simulated SAR imagery. Using a number of commonly used metrics, the performance of the proposed technique is shown to surpass that of existing speckle-noise-filtering methods such as the Gamma MAP, the modified Lee, and the enhanced Frost.

© 2006 Optical Society of America

**OCIS Codes**

(030.0030) Coherence and statistical optics : Coherence and statistical optics

(100.0100) Image processing : Image processing

(110.0110) Imaging systems : Imaging systems

(280.0280) Remote sensing and sensors : Remote sensing and sensors

**ToC Category:**

Atmospheric and Oceanic Optics

**History**

Original Manuscript: June 1, 2005

Revised Manuscript: November 21, 2005

Manuscript Accepted: December 18, 2005

**Citation**

Ousseini Lankoande, Majeed M. Hayat, and Balu Santhanam, "Scene estimation from speckled synthetic aperture radar imagery: Markov-random-field approach," J. Opt. Soc. Am. A **23**, 1269-1281 (2006)

http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-23-6-1269

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