A novel wavelet thresholding rule for speckle reduction from ultrasound images
Leena Jain, Palwinder Singh
Abstract
The speckle noise is the major area of concern in ultrasound imaging. Speckle degrades the speed and accuracy of subsequent image processing tasks such as segmentation, description etc. But reduction of speckle may cause blurring or loss of edges and important features. In our work, we have employed a novel thresholding rule based on wavelet transform for speckle reduction from ultrasound images. The wavelet transform performs multi-scale analysis of the given image by treating different frequency components present in an image separately. The experiment results exhibit that the proposed thresholding rule gives better results for speckle reduction, edge preservation and feature preservation for medical ultrasound images, as compared with the existing thesholding rules.