Systholic Boolean Orthonormalizer Network in Wavelet Domain for SAR Image Despeckling

TL;DR

This paper introduces a novel wavelet domain despeckling method for SAR images using a Systholic Boolean Orthonormalizer Network to effectively reduce speckle noise, demonstrating superior results compared to existing techniques.

Contribution

It proposes a new despeckling approach combining wavelet transform, bit-slicing, and SBON for improved SAR image noise reduction.

Findings

Outperforms most current despeckling methods.

Effectively removes speckle noise of unknown variance.

Preserves image details while reducing noise.

Abstract

We describe a novel method for removing speckle (in wavelet domain) of unknown variance from SAR images. The me-thod is based on the following procedure: We apply 1) Bidimentional Discrete Wavelet Transform (DWT-2D) to the speckled image, 2) scaling and rounding to the coefficients of the highest subbands (to obtain integer and positive coefficients), 3) bit-slicing to the new highest subbands (to obtain bit-planes), 4) then we apply the Systholic Boolean Orthonormalizer Network (SBON) to the input bit-plane set and we obtain two orthonormal output bit-plane sets (in a Boolean sense), we project a set on the other one, by means of an AND operation, and then, 5) we apply re-assembling, and, 6) re-sca-ling. Finally, 7) we apply Inverse DWT-2D and reconstruct a SAR image from the modified wavelet coefficients. Despeckling results compare favorably to the most of methods in use at the moment.