Title :
Bayesian despeckling to SAR images based on the membrane MRF model
Author :
Song Heng ; Wang Shi-Xi ; Ji Ke-feng ; Yu Wen-Xian
Author_Institution :
NUDT, Changsha
Abstract :
SAR imagery can be modeled as the multiplication of the noise-free image and speckle noises. So the noise-free image can be estimated from the observed image with the Bayesian estimation. It´s crucial to choose a proper prior model for well matching the SAR images´ characteristics. In this article the Membrane MRF model is employed to model the prior information, which overcomes the GMRF´s sensitivity to parameters. Simultaneously, the pixels in the homogeneous or in regions with structures are processed by adjusting the model´s neighborhood adoptively. Experiments show that not only the image is despeckled effectively but also the structures are preserved well.
Keywords :
Bayes methods; Markov processes; image denoising; radar imaging; synthetic aperture radar; Bayesian estimation; Markov random field; SAR image; image despeckling; membrane MRF model; noise-free image; synthetic aperture radar; Backscatter; Bayesian methods; Biomembranes; Educational institutions; Image edge detection; Image retrieval; Layout; Radar imaging; Speckle; Stochastic processes;
Conference_Titel :
Synthetic Aperture Radar, 2007. APSAR 2007. 1st Asian and Pacific Conference on
Conference_Location :
Huangshan
Print_ISBN :
978-1-4244-1188-7
Electronic_ISBN :
978-1-4244-1188-7
DOI :
10.1109/APSAR.2007.4418623