Publication Type:

Conference Proceedings

Source:

proceedings of the IEEE International Conference on Communication and Signal processing, ICCSP 2014 (2014)

Keywords:

Denoising, Geman-McClure estimation function, Maximum likelihood estimation, Non local means, PSNR, SSIM, Synthetic Aperture Radar(SAR)

Abstract:

Image denoising is an important problem in image processing because noise may interfere with visual interpretation. This may create problems in certain applications like classification problem, pattern matching, etc. This paper presents a new approach for image denoising in the case of speckle noise models. The proposed method is a modification of Non Local Means filter method using Maximum Likelihood Estimation. The Non Local Means algorithm performs a weighted average of the similar pixels. Here we introduce a method that performs weighted average on restricted local neighborhoods. More over the method performs weight calculation using Geman-McClure estimation function rather than the exponential function because of the fact that Geman-McClure estimator is better in preserving edge details than the exponential function. Experiments at various noise levels based on PSNR values and SSIM values show that the proposed method outperforms the existing methods and thereby increasing the accuracy of further processing for synthetic aperture radar (SAR) images.

Cite this Research Publication

Jyothisha J. Nair and Bhadran, B., “Denoising of SAR Images Using Maximum Likelihood Estimation”, proceedings of the IEEE International Conference on Communication and Signal processing, ICCSP 2014. 2014.

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