Efficient and robust similarity measure for denoising ultrasound images in non-local framework

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Abstract
Denoising of medical image modalities is one among the foremost basic issues in medical image process. Medical modalities such as ultrasound images suffer from multiplicative speckle noise. This noise consequently reduces the contrast of ultrasound images and adversely affects the other medical image processing tasks such as medical image registration, image super-resolution, and image segmentation. Therefore, one of the important objectives of any denoising algorithm is to attenuate the speckle noise effectively and also preserve the significant medical details in the denoised image. The main focus of this paper is the reduction of speckle noise for ultrasound images using various similarity measures in non-local framework. Through exhaustive experiments conducted on real ultrasound images, B-mode and simulated synthetic images demonstrate that, the Square chord and Chi-square distance-based similarity measures are the most effective similarity measure used in non-local framework for denoising of ultrasound images.

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