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机构地区:[1]中山大学新华学院,广州510520
出 处:《生物医学工程学杂志》2014年第3期493-498,共6页Journal of Biomedical Engineering
摘 要:针对现有医学图像中存在噪声干扰与边缘信号弱等现象,本文通过对二维小波变换进行研究,同时结合图像的边缘的方向性与小波系数的相关性,提出一种基于小波特性与边缘模糊检测的医学图像处理算法。该算法通过改进小波变换与传统边缘模糊检测算法,来提高算法的降噪能力与边缘优化效果。结果表明,其实验结果与预测目标基本相符,该算法能够有效的降低医学图像中的噪声信号同时有效的保留图像的边缘信号,具有清晰度高、降噪能力强等优点。To solve the problems of noise interference and edge signal weakness for the existing medical image, we used two-dimensional wavelet transform to process medical images. Combined the directivity of the image edges and the correlation of the wavelet coefficients, we proposed a medical image processing algorithm based on wavelet char- acteristics and edge blur detection. This algorithm improved noise reduction capabilities and the edge effect due to wavelet transformation and edge blur detection. The experimental results showed that directional correlation im- proved edge based on wavelet transform fuzzy algorithm could effectively reduce the noise signal in the medical image and save the image edge signal. It has the advantage of the high-definition and de-noising ability.
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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