Optimum morphological filtering to remove speckle noise from SAR images

Alok R. Kher; Sunanda Mitra

doi:10.1117/12.146651

23 June 1993 Optimum morphological filtering to remove speckle noise from SAR images

Alok R. Kher, Sunanda Mitra

Proceedings Volume 2030, Image Algebra and Morphological Image Processing IV; (1993) https://doi.org/10.1117/12.146651
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

Abstract

Speckle together with usual additive noises cause severe degradation of Synthetic Aperture Radar (SAR) images. Spatial averaging is the commonly used technique for removing speckle noise. However, this technique reduces image resolution appreciably and as a result the image is blurred. Morphological closings and openings offer a better way to reduce the speckle noise without blurring the image. In this paper we have introduced new operators to remove dark or bright spots which can not fit inside the boundary of a convex 2D structuring element. Any region that can not fit inside the boundary is preserved. A multiscale filtering process is required to remove noise spots of different sizes. While using samples images for processing at higher scales, a preprocessing is required before the sampling to retain important image features that may be lost in sampling. Finally, the paper presents an algorithm that ensures that no distortion is introduced in the final image as a result of intermediate sampling and reconstruction steps. We have used this algorithm to filter the noise in SAR images obtained at different wavelengths. The present technique is remarkably more successful in restoring complex image details than either spatial averaging or morphological filtering using median operators.

Citation Download Citation

Alok R. Kher and Sunanda Mitra "Optimum morphological filtering to remove speckle noise from SAR images", Proc. SPIE 2030, Image Algebra and Morphological Image Processing IV, (23 June 1993); https://doi.org/10.1117/12.146651

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