Speckle Suppression of Radar Images Using Normalized Convolution
A. K. Helmy and G. S. El-Taweel
DOI : 10.3844/jcssp.2010.1154.1158
Journal of Computer Science
Volume 6, Issue 10
Problem statement: Synthetic Aperture Radar (SAR) images are becoming more widely used in remote sensing applications. SAR uses microwave radiation to illuminate the earth's surface. The coherent microwave illumination, however, suffers from fading effects result in generating a multiplicative speckle noise that corrupts SAR images. Approach: Through this study, scheme to reduce speckles was proposed, it was designed to accomplish the following goals: Reduction of variance in homogeneous areas, side by side with preservation of edges and lines. Our scheme estimates data samples where speckles were resided from samples on regularly shifted sampled grid of original SAR image. Firstly, median filter was first applied on the original SAR image. Secondly, edge enhanced filter was applied to the median filtered image. Then the filtered images (median and edge enhanced median images) were spatially shifted a with respect to the original SAR image. Lastly, Noise-free SAR image was derived through a projection of down sampled shifted images (median filtered, edge enhanced of median filtered and original SAR Image) onto a subspace using Normalized Convolution (NC). This led to more samples of the same modality being gathered for the analysis (smoothness through applying median filter, edges from enhancement of median filter and original SAR samples), which in turn improves signal-to-noise ratio and reduces diffusion across discontinuities. Results: Proposed scheme produces same variance level in smoothed area as other statistical filter, about 0.12 higher than the best of statistical filter. On the other hand it surplus other statistical filters in preserving fine detail as it produce 33 and 27% higher than the best reading of the statistical filter in ENL and DR values respectively. Conclusion: The proposed scheme produced compromise results of speckles reduction and preserving level of fine details that have an important factor in further image processing and interpretation.
© 2010 A. K. Helmy and G. S. El-Taweel. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.