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Interference-based speckle filter

Speckle noise is a random granular texture produced by mutual interference of a set of scattered wavefronts, so it is inherent to ultrasonic imaging. Depending on the phase of the wavefronts, the interference may be constructive or destructive. In this work, we developed an interference based speckle filter (ISF), whose first step is to attenuate the destructive interference, because it carries little information about the imaged structures. In order to do that, we considered, for each pixel, the maximum between the median and the original value. To eliminate the remaining bright speckles, we applied a median filter. The resulting image had minimized speckle effects. We have created two basic numeric phantoms, a linear array ultrasound and an intravascular ultrasound phantoms, and we have simulated 20 random initializations of speckle noise for each phantom. Then, we filtered the noisy images using several filters: ISF, median, Wiener, anisotropic diffusion and speckle reducing anisotropic diffusion (SRAD). To evaluate and compare their performances, we have calculated mean and standard deviation of a homogeneous region, square root mean error and structural similarity (SSIM) for each one. ISF presented an overall 0.91 rate for SSIM, while SRAD and Wiener filter performed SSIM 0.87 and 0.85 rates, respectively. This filter is easy to implement, because it requires only a sequence of three basic operations (Median, MaxValue and Median) and it is also easy to set the input parameters (the two radii of the median filters). Mostly important, it is able to smooth speckle effects without blurring edges.