Edge-Based Automatic Parameter Selection for Sub-Optimal Image Despeckling Using Kuan Filter

Multiplicative speckle noise is a common problem found in several imaging applications, mainly in SAR and ultrasound imaging. This paper targets the Kuan despeckling filter and seeks to optimize its output without the need for several runs of the filter with the parameters adjusted each time. The proposed solution estimates 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.