Parameter estimation of heavy-tailed rayleigh prior model from observed SAR amplitude images

Zengguo Sun, Ram Mohan Narayanan, Chongzhao Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We propose a new method for estimating the parameters of heavy-tailed Rayleigh prior model from the observed synthetic aperture radar (SAR) amplitude images. First, we change the multiplicative SAR image model into an additive one using logarithmic transformation. Next, we derive the expectation and variance of the log-transformed image using negative-order moments concept. Finally, we obtain the above quantities for two kinds of SAR amplitude images: the squareroot of intensity image and the multi-look averaged amplitude image. Particularly for the latter, we derive the closed-form expressions for such expectation and variance based on the Gaussian approximation of the log-transformed speckle. Monte Carlo simulation results demonstrate that the proposed estimators, which are easy to implement with the analytical expressions, are efficient for the parameter estimation of the heavy-tailed Rayleigh prior model from the observed image.

Original languageEnglish (US)
Title of host publication2008 5th European Radar Conference Proceedings, EuRAD 2008
Pages360-363
Number of pages4
StatePublished - 2008
Event2008 5th European Radar Conference, EuRAD 2008 - Amsterdam, Netherlands
Duration: Oct 30 2008Oct 31 2008

Other

Other2008 5th European Radar Conference, EuRAD 2008
CountryNetherlands
CityAmsterdam
Period10/30/0810/31/08

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Parameter estimation of heavy-tailed rayleigh prior model from observed SAR amplitude images'. Together they form a unique fingerprint.

  • Cite this

    Sun, Z., Narayanan, R. M., & Han, C. (2008). Parameter estimation of heavy-tailed rayleigh prior model from observed SAR amplitude images. In 2008 5th European Radar Conference Proceedings, EuRAD 2008 (pp. 360-363). [4760876]