Noise Reduction in Synthetic Aperture Radar Imagery Using a Morphology-Based Nonlinear Filter

Mark A. Schulze and Qing X. Wu

Landcare Research New Zealand
Wellington, New Zealand

Presented at DICTA95, Digital Image Computing: Techniques and Applications, Conference of the Australian Pattern Recognition Society

Brisbane, Queensland, Australia
December 6-8, 1995

Final Published Abstract

Complete reference:
M. A. Schulze and Q. X. Wu. "Noise reduction in synthetic aperture radar imagery using a morphology-based nonlinear filter." Proceedings of DICTA95, Digital Image Computing: Techniques and Applications pp. 661-666. (Brisbane, Australia, December 6-8, 1995.)

Speckle noise is a multiplicative process that is the primary source of corruption in coherently illuminated imaging modalities, including synthetic aperture radar (SAR). Theoretically, the ratio of the standard deviation to the signal value, the "coefficient of variation," is constant at every point in images corrupted by purely multiplicative noise. We introduce a new nonlinear filter based on mathematical morphology that uses this property to remove speckle noise from SAR images without blurring edges. The filter performs low-pass filtering over areas in an image where the coefficient of variation is small. Since edges and other image features usually increase the estimated coefficient of variation, the new filter smooths homogeneous regions of the image and enhances contrast at edges. Examples are given comparing the new filter to established speckle noise reduction methods on SAR images.

© Copyright 1995.

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