De-noising method for echocardiographic images based on the second-generation curvelet transform

Abstract

As a novel multiscale transform, curvelet transform has the ability to give a better sparse representation of images with singularity along curves. After analyzing the second-generation curvelet transform, this work presents a new de-noising technique for echocardiographic images corrupted with speckle noise. We employed this new technique, nonlinear diffusion based on total variation, to suppress artifacts resulting from curvelet transform. The results show that this method gives better performance in noise suppression while preserving the edges of echocardiographic images, compared to existing methods. The application of curvelet transform reveals its great potential in echocardiographic image processing.