| 引用本文: | 王春光,高广珠,余理富,等.基于小波分析的子带特征提取与选择方法.[J].国防科技大学学报,2006,28(1):85-89.[点击复制] |
| WANG Chunguang,GAO Guangzhu,YU Lifu,et al.Feature Extraction and Choice Based on MCSF of Wavelet Multi-scale Transform[J].Journal of National University of Defense Technology,2006,28(1):85-89[点击复制] |
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| 基于小波分析的子带特征提取与选择方法 |
| 王春光, 高广珠, 余理富, 何智勇 |
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(国防科技大学 电子科学与工程学院，湖南 长沙 410073)
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| 摘要: |
| 在研究了目标图像多尺度小波分解特性的基础上,提出了基于小波多尺度分解子带主成分的特征提取的算法。该算法利用图像在不同尺度的小波变换域中能量局部集中性，选择各子带能量较集中的局部小波系数构成图像目标特征向量。这种特征包含图像目标的主要边缘、纹理、灰度、结构等多种信息。由于对图像目标的特征信息的分布没有任何限制，因而适用于多种类型的图像的特征提取，可以解决单一特征提取方法中必须面对的所提取特征不明显的难点。这种特征向量对噪声有较好的鲁棒性。 |
| 关键词: 小波多尺度分解 图像处理 特征提取 子带主成分 |
| DOI： |
| 投稿日期：2005-10-12 |
| 基金项目: |
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| Feature Extraction and Choice Based on MCSF of Wavelet Multi-scale Transform |
| WANG Chunguang, GAO Guangzhu, YU Lifu, HE Zhiyong |
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(College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China)
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| Abstract: |
| Based on an analysis of the wavelet multi-scale transform in target image, this paper puts forward a new method to extract the main features of the transform. It, in terms of the energy concentricity of the image's wavelet coefficients, selected the parts with concentrated energy to construct the feature vectors, which include most of the edge, texture, luminance and structure features. As there is no limit to the distribution of the image feature information, the method can be used in many kinds of image feature extraction, thus solving the problem of feature illegibility with which the single-feature extraction is confronted. In the experiment, normal white noises with different ranges were added to the images and the result approves that the feature vectors are robust to noise. |
| Keywords: wavelet multi-scale transform image processing feature extraction MCSF(main coefficient of sub-frequency |
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