A Novel Ultrasound Image Enhancement Algorithm Using Cascaded Clustering on Wavelet Sub-bands

The high content of speckle artifacts in ultrasound images affects edges, fine details, and contrast of the image, which in turn affects the accuracy of clinical analysis and diagnostic interpretation. This paper gives importance to preserving valuable edge information in the image and proposes a novel clustering algorithm on wavelet transformed sub-bands for speckle noise suppression. The processing pipeline consists of several stages including edge detection using Canny edge detector, speckle noise separation using LOG transform, wavelet transformation and clustering, and inverse transforms to produce the filtered output. This paper also presents experimental analysis and quantitative evaluation of results to demonstrate the effectiveness of the proposed approach.