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投稿时间：2007-11-30
投稿时间：2007-11-30
中文摘要: 在皮肤症状自动诊断系统中,为了消除图像中皮肤表面的毛发与纹理对识别系统的干扰,分析了小波变换的特点,将塔型小波变换和树型小波变换进行了比较,并根据皮肤显微图像一阶分解后得到的4个子图能量分布情况,提出了基于塔型分解的模极大值小波域的去噪声算法.实验证明,该算法对皮肤显微图像去噪效果较好.
Abstract:In the research of Skin Micro-image Processing System, the characters of pyramid-structured and tree-structured wavelet transform are compared. According to the energy distributing of four sub-images after the first level wavelet decomposing, a denoising algorithm based on modulus maximum wavelet field is put forward to remove hair and texture from skin Micro-image. Experimental results are satisfactory.
文章编号：20080111 中图分类号： 文献标志码：
基金项目:
| 作者 | 单位 |
| 赵倩 | 上海电力学院 计算机与信息工程学院, 上海 200090 |
| Author Name | Affiliation |
| ZHAO Qian | School of Computer and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China |
引用文本：
赵倩.基于小波变换的皮肤显微图像去噪算法的研究[J].上海电力大学学报,2008,24(1):38-42.
ZHAO Qian.Denoise Algorithm Research of Skin Micro-image Based on Wavelet Transform[J].Journal of Shanghai University of Electric Power,2008,24(1):38-42.
赵倩.基于小波变换的皮肤显微图像去噪算法的研究[J].上海电力大学学报,2008,24(1):38-42.
ZHAO Qian.Denoise Algorithm Research of Skin Micro-image Based on Wavelet Transform[J].Journal of Shanghai University of Electric Power,2008,24(1):38-42.