An undecimated wavelet based adaptive fusion filtering for ultrasound despeckling

Abstract

An efficient fusion based speckle denoising algorithm is proposed in this paper to improve the edge and detail preservation of US images. This is accomplished by integrating complementary information from two wavelet despeckled source images. The two source images are such that one denoise the coefficients greater than threshold for improving the noise removal performance and another denoise the coefficients below threshold to preserve the fine details. For fusion, a two stage fusion algorithm utilizing a novel fusion rule exploiting the inter and intra scale dependency of the wavelet coefficients is proposed. The first stage performs an interscale activity based fusion and the second stage accomplishes an intra scale dependency based fusion for fusing the detail subbands of the two images. The approximation coefficients are fused with a maximum rule. The resulting fused image give an outstanding performance compared with existing wavelet based approaches and other fusion techniques in terms of Peak-Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index Measure (SSSIM), Equivalent Number Of Looks (ENL) And Edge Preservation Index (EPI).