葛明达, 孙剑峰, 王天骄, 王骐. 基于对比度调制法对条纹管激光雷达距离像的去噪方法[J]. 红外与激光工程, 2013, 42(6): 1448-1452.
引用本文: 葛明达, 孙剑峰, 王天骄, 王骐. 基于对比度调制法对条纹管激光雷达距离像的去噪方法[J]. 红外与激光工程, 2013, 42(6): 1448-1452.
Ge Mingda, Sun Jianfeng, Wang Tianjiao, Wang Qi. Denoising methods for streak tube imaging lidar range image based on contrast-modulation method[J]. Infrared and Laser Engineering, 2013, 42(6): 1448-1452.
Citation: Ge Mingda, Sun Jianfeng, Wang Tianjiao, Wang Qi. Denoising methods for streak tube imaging lidar range image based on contrast-modulation method[J]. Infrared and Laser Engineering, 2013, 42(6): 1448-1452.

基于对比度调制法对条纹管激光雷达距离像的去噪方法

Denoising methods for streak tube imaging lidar range image based on contrast-modulation method

  • 摘要: 激光雷达的距离像是雷达成像系统区别于其他的成像系统(如红外成像系统、可见光成像系统)所特有的信息,它是对目标精确识别、打击的基础。如何对距离像去噪直接决定了下一步目标定位、识别的精确性。针对雷达距离像的特点,提出了一种基于对比度调制方法对条纹管激光雷达的距离像去噪方法,通过提取距离像噪声的对比度信息,用其调制未经过去噪的距离像,从而得到距离像中的噪声图像,最后用未经过处理的距离像减去噪声图像,得到图像即为去噪后距离像。研究表明该方法去噪效果明显,在去噪的同时很好地保持了距离像的边缘信息,去噪后图像的信噪比明显提高,距离像的属性也没有改变,这是其他方法对距离像去噪所不具有的优点。

     

    Abstract: Lidar range image is particular information of lidar system that other imaging systems (such as IR imaging system and optical imaging system) can not provide. It is the foundation for precision target identification and attacking. How to denoise directly determines the accuracy of target recognition. According to the characteristics of the radar range image, a method was presented for streak tube imaging lidar based on contrast-modulation method. The noise contrast information of range image was extracted to modulate original image, so as to get noise image, and finally range image without processing was used to minus the noise image to get the image which was denoised. The research result shows that the effect of this denoising method is obvious and the edge information of range image also keeps intact. After denoising, the signal noise ratio (SNR) of the range image is significantly improved. The attributes of range image does not change. This is the advantage the other methods for range image denoising methods does not have.

     

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