Multitemporal SAR image despeckling based on non-local theory

In this paper, a multitemporal SAR image despeckling based on non-local theory (NLG-MulSAR) algorithm is proposed, which improved the basic framework of ratio-based denoising (RABASAR). The temporal and spatial information integrated. super ratio acquisition part RABASAR are optimized by NLG filtering algorithm. does not need to transform multiplicative noise into additive synthetic aperture radar (SAR) then filter it. uses nonlinear method eliminate influence strong points while preserving edge features. Based number pixels in block, avoids generation fuzzy filtered image. study, we use seven Gaofen three images captured at different times Beijing area as experimental data evaluate effect methods terms five objective parameters: signal-to-noise ratio, standard deviation, equivalent looks, radiative resolution, speckle index. addition, image, propose an index, namely coefficient retention characteristics results show that compared with algorithm, proposed NLG-MulSAR can better balance relationship between texture detail attenuate protecting