小波不变矩的低空风切变识别

针对微下击暴流、低空急流、顺逆风以及侧风低空风切变样本图像间的形状特性关系,主要研究了小波不变矩的特征提取技术在风切变识别中的应用.首先,采用基于三次B样条的小波不变矩提取风切变图像的形状特征.然后,将提取的特征通过Fisher线性判别分析(LDA)降低维数,实现风切变有效特征的提取.最后,采用三阶近邻分类器分类识别四种低空风切变.实验结果表明,该算法与应用Hu矩和Zernike矩特征进行分类识别相比,识别结果更加稳定,且平均识别率得到了较大提高,能够有效用于风切变图像的类型识别中.

Recognition on low-level wind shear of wavelet invariant moments

According to the shape characteristic relationship within microburst, low-level jet stream, side wind shear and tailwind-or- headwind shear images, the feature extraction technique of wavelet invariant moment applied to the recognition of wind shear was mainly studied. Firstly, wavelet invariant moments method was employed to extract shape features of low-level wind shear images, which was based on cubic B- spline wavelet basis. Then, the feature dimensions were reduced by Fisher Linear Discriminative Analysis(LDA) in order to get the effective shape features of target images. Finally, the effective shape features were fed into 3-nearest neighbor classifier to identify four types of low-level wind shear. The experiment results demonstrate that the proposed approach has stronger robustness and better average recognition rate compared to the recognition effect based on Hu moment and Zernike moment, which can effectively be used to recognize the type of wind shear images.