Regularized speckle reducing anisotropic diffusion for feature characterization

For tissue characterization in medical ultrasound imagery or terrain characterization in synthetic aperture radar imagery, it is necessary to preprocess imagery to reduce granular, texture-alike noise called speckle. This preprocessing is difficult when it is needed to preserve delicate image details that are buried in speckle. Speckle reducing anisotropic diffusion (SAR) is a partial differential equation-based method developed for this purpose. Toward its improved performance for point/linear features, we introduced a novel regulator called energy condensation integral and developed a regularized SRAD (Reg-SRAD) via minimization. The Reg-SRAD generates outputs with increased resolution for point and linear features while retaining the characteristics the SRAD-filtering speckle with regional features enhanced. The performance of the method has been illustrated using synthetic and real ultrasound data, and radar imagery as well.