Tezture Analysis of Ultrasonic Image Based on Wavelet Packet Denoising and Feature Eztraction

摘要：

The paper introduces a kind of approach for ultrasonic image categorization based on wavelet packet denoising and texture analysis. Firstly, the texture image denoising method based on wavelet packet transform modulus maximum is adopted aiming at texture images of complicated texture and abundant details. The method can maintain image details at the same time of denoising. Then by using gray level co-occurrence matrix (GLCM) method, parameters in four directions which can represent images texture feature efficiently are extracted: energy, contrast, entropy and inverse difference moment. Finally neural network is used to identify two kinds of images according to extracted characteristic parameters and achieves good effects.

关键词： Image Denoising Waveletet Modulus Mazimum Tezture Analysis Gray Level Co-occurrence Matriz Feature Eztraction

作者: Yali Huang Xiaojun Zhao Qingshun Zhang Fang Wang Zhen Zhao

作者单位: College of Electronic and Informational Engineering,Hebei University Department of Function,Affiliated Hospital of Hebei University Baoding,China

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-6

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）