Improvement of Ultrasound Image Based on Wavelet Transform: Speckle Reduction and Edge Enhancement

For 2-dimensional B-mode ultrasound images, we propose an image enhancement algorithm based on a multi-resolution approach. In the proposed algorithm, we perform the directional filtering and noise reducing procedures from the coarse to fine resolution images that are obtained from the wavelet-transformed data. For directional filtering, the structural feature at each pixel is examined through the eigen-analysis. Then, if the pixel belongs to the edge region, we perform two-step directional filtering, namely, directional smoothing along the tangential direction of the edge to improve its continuity, and directional sharpening along the normal direction to enhance the contrast. Meanwhile, speckle noise is alleviated by reducing the wavelet coefficients corresponding to the homogeneous region. The reducing rate of the wavelet coefficients is determined by considering the frequency characteristics of speckle. Thereby, the algorithm reduces speckle noise efficiently without affecting the edge sharpness and enhances edges regardless their size. Note that the proposed speckle reduction scheme is based on the structural information rather than the statistics of the magnitude of wavelet coefficients as in the existing methods. The proposed algorithm is compared to the algorithm based on nonlinear anisotropic diffusion filtering and the one based on the wavelet shrinkage scheme. The experimental results show that the proposed algorithm considerably improves the subjective image quality without providing any noticeable artifact.