Speckle Reduction Algorithm for Medical Ultrasound Imaging

Image denoising has remained a fundamental problem in the field of medical image processing. Ultrasound images are most commonly used in medical diagnostics. Unfortunately the quality of ultrasound imaging is degraded by the presence of signal dependent noise called speckle noise. It is necessary to apply an efficient despeckling technique to compensate for data corruption. Recently, wavelet and multi scale based methods, due to their excellent localisation property, have rapidly become very popular for image denoising. In this paper, a new noise variance estimation technique is proposed which attempts to map the median value of the pixelwise noise standard deviation. Then, an adaptive threshold is applied to shrink the noisy coefficients. The experimental results show that the proposed algorithm performs well for different ultrasound images and over a large range of noise variances.