摘要： 介绍了一种红外双色目标识别算法。该算法将通过二维傅立叶小波变换对图像提取的特征作为特征向量，这组特征向量具有旋转、平移和尺度不变性。利用Dempster-Shafer(D-S)证据理论进行图像融合，并使用神经网络分类器进行分类。实验结果表明，该算法提高了对近似物体的识别能力，能对飞机、舰船等目标进行有效的识别。

关键词: 红外双色, 目标识别, 傅立叶小波变换, 神经网络

Abstract: This paper proposes an algorithm of infrared bicolor target recognition, in which 2D Fourier-wavelet transform is applied to extract the features of image, and the Fourier-wavelet description for the object recognition is regarded as vector characteristics, characterized with invariancy to translations, scaling and rotation. It improves the rate of target recognition by using D-S theory and netural network classifier. Experimental results show this algorithm can identify the aircraft and the warship objects effectively.

Key words: infrared bicolor, target recognition, Fourier-wavelet transform, netural network

中图分类号: 

• TP391