An enhanced Kuan filter for suboptimal speckle reduction

Speckle noise is a common problem found in several imaging applications, mainly in SAR and ultrasound imaging. Originally designed for RADAR and SONAR image denoising, the Kuan filter can be adapted for other applications by emulating its parameters. However, these parameters need to be calibrated for each image by applying the filter several times with the parameters modified upon each filter run, until the desired quality is reached. In this paper, we propose a novel technique for automatically estimating the optimal filter parameter value, which results in near-optimal performance, where the PSNR loss does not exceed 0.1 dB most of the time, compared to the best possible filter output, and yielding a significant gain with respect to the basic filter used with the default parameters.