A Fast Non-destructive Algorithm for Image Description Based on Improved Wavelet Moment Features
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摘要: 为了更有效地利用小波矩不变量算法来快速无损地计算图像特征值, 提出了一种融合Mallat算法的无损采样的新型小波矩不变量算法. 在此基础之上, 结合傅里叶变换的原理及特点, 提出了基于频率幅值谱与小波矩不变量的特征提取方法. 并将改进的小波矩不变量算法与传统使用三次B样条矩的小波矩、Hu矩进行了比较. 实验表明, 改进的小波矩不变量在比传统小波矩不变量算法性能几乎没有损失的情况下, 大大加快了小波矩不变量的计算速度, 并且基于频率幅值谱的小波矩有更强的抗噪性.Abstract: In order to rapidly and non-destructively calculate image eigenvalue, by combining the Mallat algorithm, a new invariant wavelet moment algorithm with non-destructive sampling is presented. Feature extraction based on amplitude spectrum and wavelet moment invariants is also presented. The experimental results show that compared with the traditional cubic B-spline wavelet moments and Hu moment invariants, this algorithm can greatly accelerate the wavelet moment invariants calculation with few losses in performance. The new wavelet moment invariants algorithm based on amplitude spectrum is verified to be insensitive to noises compared with other wavelet moment invariants.
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Key words:
- Mallat algorithm /
- wavelet moment invariants /
- feature extraction /
- amplitude spectrum
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