基于梯度天空背景的非均匀性校正和点目标探测

doi:10.13229/j.cnki.jdxbgxb201705040

吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (5): 1625-1633.doi: 10.13229/j.cnki.jdxbgxb201705040

基于梯度天空背景的非均匀性校正和点目标探测

刘让^{1, 2, 3}, 王德江^{1, 2}, 张刘⁴, 周达标^{1, 2, 3}, 贾平^{1, 2}, 丁鹏^{1, 2, 3}

1.中国科学院长春光学精密机械与物理研究所,长春 130033;
2.中国科学院航空光学成像与测量重点实验室,长春 130033;
3.中国科学院大学,北京 100049;
4.吉林大学仪器科学与电气工程学院,长春130061

收稿日期:2016-06-14 出版日期:2017-09-20 发布日期:2017-09-20
通讯作者: 张刘(1978-),男,教授.研究方向:卫星姿态测量与控制技术,空间对接测量技术及空间遥感成像系统设计与仿真技术.E-mail:zhangliu@jlu.edu.cn
作者简介:刘让(1990-),男,博士研究生.研究方向:红外探测技术,图像处理.E-mail:liurang14@mails.ucas.ac.cn
基金资助:
国家自然科学基金项目(61308099); 吉林省重大科技攻关专项项目(11ZDGG001); 国家重点研发计划(2016YFB0501003); 上海市科委重点项目(16DZ1120400)

Non-uniformity correction and point target detection based on gradient sky background

LIU Rang^{1, 2, 3}, WANG De-jiang^{1, 2}, ZHANG Liu⁴, ZHOU Da-biao^{1, 2, 3}, JIA Ping^{1, 2}, DING Peng^{1, 2, 3}

1.Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033,China;
2.Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of Sciences, Changchun 130033,China;
3.University of Chinese Academy of Sciences, Beijing 100049,China;
4.College of Instrumentation & Electrical Engineering, Jilin University, Changchun 130061, China

Received:2016-06-14 Online:2017-09-20 Published:2017-09-20

摘要/Abstract

摘要： 针对黑体两点校正方法不适用于校正梯度天空背景的问题,提出一种新的基于梯度天空背景的两点校正方法。首先,采用邻域像素替代法剔除位置固定不变的盲元;然后,利用红外焦平面探测器拍得的两幅不同俯仰角度的纯净天空图像作为两个温度点,进行两点校正获得增益系数和偏置系数;最后,通过修正这两个系数剔除少量随机噪点。实验结果验证了该方法的有效性。本文在校正基础上还提出了一种小窗口双边滤波和梯度模板联合检测算法,用于探测暗弱点目标。首先采用小窗口的双边滤波去除高斯噪点,然后与梯度模板做卷积,自适应阈值分割检测出暗弱点目标。实验结果表明,提出的模板算法对复杂背景的抑制作用较强,可有效提高目标的信噪比,而且算法复杂度不高,易于实时实现。

关键词: 信息处理技术, 梯度天空背景, 非均匀性校正, 梯度模板算法, 暗弱点目标

Abstract: Tow-point Non-uniformity Correction (NUC) based on blackbody is not suitable to correct actual sky background. To overcome this problem, a new two-point correction method based on gradient sky background was proposed. First, the fixed positions of bind pixels are replaced by the pixels in neighborhood. Then, the two-point images are captured at two different pitch angles in the pure sky by infrared focal plane array detector; and gain and offset coefficients are obtained from two-point correction. Finally, the two correction coefficients are modified to remove a few remaining bas points. Results show that this method has good performance. In the second place, a new bilateral filtering and gradient template algorithm is proposed to detect dim point target after correction. First, median filter is used to remove remaining single noise. Then, convolution with the gradient template is made. Dim point target can be detected after adjusting image grayscale to the certain threshold interval. Results show that the proposed gradient template algorithm has advantages to suppress complex background. It improves Signal-to-noise Ratio (SNR), and has the preference of low complexity and easy implementation in real-time system.

Key words: information processing technology, gradient sky background, non-uniformity correction, gradient template algorithm, dim point target

中图分类号:

TP391.4

刘让, 王德江, 张刘, 周达标, 贾平, 丁鹏. 基于梯度天空背景的非均匀性校正和点目标探测[J]. 吉林大学学报(工学版), 2017, 47(5): 1625-1633.

LIU Rang, WANG De-jiang, ZHANG Liu, ZHOU Da-biao, JIA Ping, DING Peng. Non-uniformity correction and point target detection based on gradient sky background[J]. 吉林大学学报(工学版), 2017, 47(5): 1625-1633.

参考文献

[1] 余毅,常松涛,王旻,等.宽动态范围红外测量系统的快速非均匀性校正[J]. 光学精密工程,2015,23(7):1932-1938.
Yu Yi,Chang Song-tao,Wang Min,et al. Fast non-uniformity correction for high dynamic infrared radiometric system[J]. Optics and Precision Engineering,2015,23(7):1932-1938.
[2] 王刚,陈永光,杨锁昌,等. 采用图像块对比特性的红外弱小目标检测[J].光学精密工程,2015,23 (5):1424-1433.
Wang Gang,Chen Yong-guang,Yang Suo-chang, et al. Detection of infrared din small target based on image patch contrast[J]. Optics and Precision Engineering, 2015,23(5):1424-1433.
[3] 宁永慧,郭永飞,曲利新,等. 多通道时间延迟积分CCD辐射标定和像元实时处理[J]. 光学精密工程,2015,23(10):2952-2961.
Ning Yong-hui,Guo Yong-fei,Qu Li-xin, et al. Radiometric calibration and pixel data real-time processing of multi-tip TDICCD[J]. Optics and Precision Engineering,2015,23(10):2952-2961.
[4] 殷世民,相里斌,周锦松.辐射源标定红外焦平面阵列非均匀性校正算法研究[J].光子学报,2008,37(5):992-995.
Yin Shi-min,Xiang Li-bin, Zhou Jin-song, et al. Research on non-uniformity correction of IRFPA based on radiaion source scaling[J]. Acta Photonica Sinica,2008,37(5):992-995.
[5] 白俊奇,陈钱.基于环境温度的红外焦平面阵列非均匀性校正[J].红外与毫米波学报,2010,29(1):50-52.
Bai Jun-qi, Chen Qian. Nonuniformity correction for infraredfocalplane arrays based on environment temperature[J]. Journal of Infrared and Millimeter Waves,2010,29(1):50-52.
[6] Cao Yan-peng, Christel Tisse. Single-image basedsolution for optics temperature-dependent nonuniformity correction in an uncooled long-waveinfraredcamera[J].Optics Letters,2014,39(3):646-648.
[7] Guadagnoli E,Giunti C, Porta A . Thermal imager non-uniformity sources modeling[C]∥Proceedings of the SPIE, Orlando, Florida, United States,2011:1-12.
[8] 张昊,刘振国,胡晓梅,等. 场景主动运动控制的非均匀性校正方法[J].红外与激光工程,2011,40(3):397-401.
Zhang Hao, Liu Zhen-guo, Hu Xiao-mei, et al. Nonuniformity correction based on active movement-control of scene[J].Infrared and Laser Engineering, 2011,40(3):397-401.
[9] Scribner D A, Sarkady K A, Caulfield J T,et al. Nonuniformity correction forstaringfocal plane arrays using scene-based techniques[J]. Proceedings of the SPIE,Washington DC,1990:224-233.
[10] Scribner D, Sarkady K A, Kruer M, et al. Adaptive retina-like preprocessing for imaging detector arrays[C]∥International Conference on Neural Networks,San Francisco,1993:1955-1960.
[11] Hayat M M, Torres S N, Cain S C, et al. Model-based real-time nonuniformitycorrection in focal plane array detectors[J]. Proceedings of the SPIE,Orlando,1998:122-132.
[12] 李庆,刘上乾, 王炳健,等.基于神经网络的RFPA 非均匀性校正新算法[J].红外与激光工程, 2007, 36(3):342-344.
Li Qing, Liu Shang-qian,Wang Bing-jian, et al. New nonuniformity correction algorithm for IRFPA based on neural network[J]. Infrared and Laser Engineering, 2007,36(3):342-344.
[13] Torres S N, Pezoa J E, Haya M M. Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form[J].Applied Optics, 2003, 42(29): 5872-5881.
[14] 何泰诚.红外焦平面非均匀性校正算法的研究[D].西安:西安电子科技大学机电工程学院,2008.
He Tai-cheng.The research for non-uniformity correction of infrared focal plane arrays[D]. Xi'an:School of Mechano-Electronic Engineering,Xidian University,2010.
[15] 修吉宏,黄浦,李军,等.大面阵彩色CCD航测相机成像非均匀性校正[J].光学学报,2013,33(7):0711003.
Xiu Ji-hong,Huang Pu,Li Jun, et al. Non-uniformity correction of large area array color CCD aerial mapping camera[J]. Acta Optica Sinica,2013,33(7):0711003.
[16] 张桥舟.智能化红外图像非均匀性校正算法及其FPGA实现[D].南京:南京理工大学电子工程与光电技术学院,2014.
Zhang Qiao-zhou. Intelligent nonuniformity correction algorithm for IRFPA and implementation by using FPGA[D].Nanjing: School of Electronic and Optical Engineering,Nanjing University of Science and Technology,2014.
[17] Huo Yuan-kai, Wei Gen, Zhang Yu-dong, et al. Anadaptive threshold for the Canny operator of edge detection[C]∥Proceedings of the Image Analysis and Signal Processing (IASP),Zhejiang,China,2010:371-374.

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基于梯度天空背景的非均匀性校正和点目标探测

Non-uniformity correction and point target detection based on gradient sky background

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