光学学报, 2017, 37 (5): 0528001, 网络出版: 2017-05-05   

基于梯度场景的非均匀校正方法

Nonuniformity Correction Method Based on Gradient Scenes
周达标 1,2,3,*王德江 1,3霍丽君 2,3刘让 1,2,3贾平 1,3
作者单位
1 中国科学院长春光学精密机械与物理研究所中国科学院航空光学成像与测量重点实验室, 吉林 长春 130033
2 中国科学院大学, 北京 100049
3 中国科学院长春光学精密机械与物理研究所, 吉林 长春 130033
摘要
长波红外探测器经常被用于机载红外预警系统中, 常受严重的非均匀性噪声干扰。为了校正探测器的非均匀性, 补偿辐射响应非线性, 提出了一种基于梯度场景的非均匀性校正方法。给出了探测器辐射响应非均匀性的观测模型; 以标准黑体和梯度场景作为参考源, 在理论上推导出校正系数表达式; 利用原理样机进行了外场实验, 并探测民航客机目标。实验结果表明:与基于黑体的两点校正方法相比, 利用本文方法进行非均匀性校正后的图像, 局部标准差峰值由8.57降低到2.39; 对于相距50.64 km的空中客车A319型客机, 目标的信杂比由4.87提高到11.22。本文算法可以有效降低图像局部标准差, 适用于机载红外预警系统。
Abstract
Long wave infrared detectors are often employed in airborne infrared early warning systems, which are often contaminated the with heavy nonuniformity noises. To correct the nonuniformity and compensate the nonlinearity of detectors, a nonuniformity correction method is proposed. The observation model of radiance nonuniformity is introduced. The correction coefficients are deduced in theory with the reference of a blackbody and a gradient scene. And, an outfield experiment with a proof-of-concept camera is performed to detect the airliners. Experimental results show that the peak value of local standard deviation of the corrected image decreases from 8.57 to 2.39, compared with the two-point correction method based on a blackbody. For the target of Airbus A319 from 50.64 km away, the signal-to-clutter ratio rises from 4.87 to 11.22. The proposed method can decrease the local standard deviation effectively, which has a significant contribution to airborne infrared early warning systems.
参考文献

[1] 孙 慧, 徐抒岩, 孙守红, 等. 光电成像传感器光子响应非均匀性噪声评价方法研究[J]. 激光与光电子学进展, 2015, 52(4): 042302.

    Sun Hui, Xu Shuyan, Sun Shouhong, et al. Research on evaluation method of optical imaging sensors’ photon response non-uniformity noise[J]. Laser & Optoelectronics Progress, 2015, 52(4): 042302.

[2] Yang F, Wang Q, Li M. Light source system for high-precision flat-field correction and the calibration of an array detector[J]. Chinese Optics Letters, 2015, 13(4): 040402.

[3] 陈 钱. 红外图像处理技术现状及发展趋势[J]. 红外技术, 2013, 35(6): 311-318.

    Chen Qian. The status and development trend of infrared image processing technology[J]. Infrared Technology, 2013, 35(6): 311-318.

[4] 孙 刚, 翁宁泉, 肖黎明, 等. 大气温度分布特性及对折射率结构常数的影响[J]. 光学学报, 2004, 24(5): 592-596.

    Sun Gang, Weng Ningquan, Xiao Liming, et al. Profile and character of atmospheric temperature[J]. Acta Optica Sinica, 2004, 24(5): 592-596.

[5] Perry D L, Dereniak E L. Linear theory of nonuniformity correction in infrared staring sensors[J]. Optical Engineering, 1993, 32(8): 1854-1859.

[6] 段程鹏, 刘 伟, 陈耀弘, 等. 多本底采样自适应非均匀校正算法[J]. 光学学报. 2016, 36(10): 1020001.

    Duan Chengpeng, Liu Wei, Chen Yaohong, et al. Multiple background sampling adaptive non-uniform correction algorithm[J]. Acta Optica Sinica, 2016, 36(10): 1020001.

[7] Sun Z, Chang S, Zhu W. Radiometric calibration method for large aperture infrared system with broad dynamic range[J]. Applied Optics, 2015, 54(15): 4659-4666.

[8] Zhou H, Qing H, Bai L, et al. Nonuniformity correction algorithm with nonlinear model for infrared focal plane arrays[J]. Infrared Physics & Technology, 2010, 53(1): 10-16.

[9] Qian W, Chen Q, Bai J, et al. Adaptive convergence nonuniformity correction algorithm[J]. Applied Optics, 2011, 50(1): 1-10.

[10] Harris J G, Yu-Ming C. Nonuniformity correction of infrared image sequences using the constant-statistics constraint[J]. IEEE Transactions on Image Processing, 1999, 8(8): 1148-1151.

[11] Hardie R C, Baxley F, Brys B, et al. Scene-based nonuniformity correction with reduced ghosting using a gated LMS algorithm[J]. Optics Express, 2009, 17(17): 14918-14933.

[12] 冷寒冰, 易 波, 谢庆胜, 等. 基于时域矩匹配的红外图像自适应非均匀性校正[J]. 光学学报, 2015, 35(4): 0410003.

    Leng Hanbing, Yi Bo, Xie Qingsheng, et al. Adaptive nonuniformity correction for infrared images based on temporal moment matching[J]. Acta Optica Sinica, 2015, 35(4): 0410003.

[13] Liu N, Qiu H. A time-domain projection-based registration-scene-based nonuniformity correction technology and its detailed hardware realization[J]. Optical Review, 2014, 21(1): 17-26.

[14] Ren J, Chen Q, Qian W, et al. Multiframe registration based adaptive nonuniformity correction algorithm for infrared focal plane arrays[J]. Journal of Infrared and Millimeter Waves, 2014, 33(2): 122-128.

[15] Zuo C, Chen Q, Gu G, et al. Scene-based nonuniformity correction algorithm based on interframe registration[J]. Journal of the Optical Society of America A, Optics Image Science and Vision, 2011, 28(6): 1164-1176.

[16] Leathers R A, Downes T V, Priest R G. Scene-based nonuniformity corrections for optical and SWIR pushbroom sensors[J]. Optics Express, 2005, 13(13): 5136-5150.

[17] Dong X, Huang X, Zheng Y, et al. A novel infrared small moving target detection method based on tracking interest points under complicated background[J]. Infrared Physics & Technology, 2014, 65(7): 36-42.

[18] Zhu F, Qin S. A moving IR point target detection algorithm based on reverse phase feature of neighborhood in difference between neighbor frame images[J]. Chinese Journal of Aeronautics, 2006, 9(3): 225-232.

[19] Trantham K, Reece T J. Demonstration of the Airy disk using photography and simple light sources[J]. American Journal of Physics, 2015, 83(11): 928-934.

周达标, 王德江, 霍丽君, 刘让, 贾平. 基于梯度场景的非均匀校正方法[J]. 光学学报, 2017, 37(5): 0528001. Zhou Dabiao, Wang Dejiang, Huo Lijun, Liu Rang, Jia Ping. Nonuniformity Correction Method Based on Gradient Scenes[J]. Acta Optica Sinica, 2017, 37(5): 0528001.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!