Short-Time Fourier Transform and Wigner-Ville Transform for Ultrasound Image De-noising through Dynamic Mask Thresholding

摘要：

New approaches to filter out multiplicative noise fromultrasound medical images are presented in this paper. Aperformance comparison is made between the Short TimeFourier Transform (STFT) and the Wigner-Ville Transform(WVT). After segmenting the image into small, overlapping,dyadic lengths segments, STFT or WVT is applied to eachsegment individually. A minimum number of coefficients perSTFT or WVT time-frequency plane is used, which has beenfound sufficient to represent the entire time-frequency plane.When applied on simulated and real ultrasound images, theseapproaches have outperformed popular nonlinear de-noisingtechniques, such as Wavelets, Total Variation Filtering andAnisotropic Diffusion Filtering. STFT provided the maximumcleaning of speckle noise, while WVT preserved the image edgesand provided maximum resolution.

作者: Jawad F.Al-Asad Alireza Moghadamjoo

作者单位: Department of Electrical Engineering and Computer Science University of Wisconsin Milwaukee, USA

会议类型: 国际会议

会议名称: The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-06-18（万方平台首次上网日期，不代表论文的发表时间）