FPGA-Based Adaptive Speckle Suppression Filter for Underwater Imaging Sonar

Underwater forward-looking imaging sonar (FLS) is widely used on stationary and moving platforms to overcome underwater visibility problems. The SONAR images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. Speckle reduction filters are necessary to optimize the images´ exploitation procedures. The results of speckle filters may vary from one sensor and one wavelength to another; therefore, no generic de-speckling algorithm exists. Several studies have been carried out on speckle noise suppression on sidescan sonar, but the problem of speckle noise suppression for FLS has not yet been covered. A comparison of the most used classical speckle suppression filters as well as advanced wavelet-based ones was carried out. The Frost filter was found to be the most adequate for FLS data, but also the most computationally complex and not suitable for real-time processing. Two novel architectures for real-time and low-power field-programmable gate array (FPGA) implementation of the Frost speckle filter for underwater imaging sonar are presented. The proposed architectures have superior performance and power efficiency compared to standard software implementation.