Edge-detection-based filter for SAR speckle noise reduction

Abstract

Some adaptive filters, such as the Kuan, Lee, minimum mean square error (MMSE) and Frost filters, have been tested on synthetic aperture radar (SAR) data without considering the level of homogeneity in the pixels. Therefore, they degrade the spatial resolution of images and smooth details, while also decreasing the speckle noise level. There are other filters, such as the enhanced Lee and gamma maximum a posteriori (MAP), that utilize the level of homogeneity, but they cannot adequately suppress speckle noise. In addition to these weaknesses, pixels surrounding a point scatterer are also treated as point scatterers due to inadequacy of the method based on evaluating the coefficient of variation for differentiating between them and the point scatterer. We have developed a new method based on the assessment of similarity of homogeneity levels in the image, incorporating edge-detection filters to identify meaningful features and an algorithm to filter the pixels surrounding point scatterers. This method, called the UNSW (University of New South Wales) adaptive filter (UAF), was compared to nine filters using different quantitative and qualitative methods. The results show the ability of the UAF to simultaneously reduce speckle and preserve details as well as its ability to filter more pixels. The effect of increasing the damping factor on speckle noise reduction performance has also been assessed using this method.

Acknowledgements

The ERS-2 SAR image was provided by Geosciences of Australia. Also, the authors wish to acknowledge Prof. Tony Milne for providing ALOS–PALSAR and JERS-1 SAR data.

Notes

Determination of the value of N that satisfies the central limit theorem is not possible for the radar image case due to the lack of information about the amplitude of individual signals which interfere within each pixel. Moreover, this value is not constant (Lopez-Martinez 2003); however, it has been mentioned that the central limit theorem will not be fulfilled if the number of scatterers is less than 10–20 (Daba and Jreije 2008).