红外图像校正与增强技术研究现状

张宝辉; 姚立斌; 张巍伟; 陈莹妍; 王润宇

红外技术, 2017, 39 (6): 481, 网络出版: 2017-07-07

红外图像校正与增强技术研究现状

The Current Research Status of Infrared Image Correction and Enhancement

论文大纲

张宝辉 ^*姚立斌张巍伟陈莹妍王润宇

作者单位

北方夜视科技集团有限公司南京研发中心, 江苏南京 211106

红外图像处理非均匀校正分辨率增强视觉增强 infrared image processing non-uniformity correction resolution improvement vision enhancement

摘要

非均匀校正和视觉增强是红外图像处理的关键性技术, 其主要是为了解决红外系统在光学、焦平面、读出电路等设计和工艺中存在的问题。基于此, 在非均匀校正方面, 概述了近年来基于场景的非均匀校正技术和去除“鬼影”现象的发展现状。在视觉增强方面, 从灰度值的动态压缩角度阐述了传统方法和红外图像细节增强技术的最新研究成果, 以及 640×512中波数字化焦平面探测器在增强方面采用的最新技术和成像效果; 并从分辨率增强角度介绍了“微扫”技术在红外系统分辨率增强方面的突破技术和相关产品。最后, 对红外图像处理发展趋势进行了展望。

Abstract

Non-uniformity correction(NUC) and vision enhancement are the key techniques of infrared image processing. They serve mainly to resolve the existed problems for infrared system in the design and technology of optics, FPA and circuit reading. In the respect of non-uniformity correction, recent advances on the technique of scenario-based non-uniformity correction, and ghosting artifact are reviewed. In the respect of vision enhancement, traditional method and the new technique of infrared image detail enhancement are expounded from the perspective of gray value dynamic compression, as well as the new imaging enhancement technique used in the MWIR 640×512 digital IRFPA detector. The breakthrough technique and related products of micro-scanning technique used in infrared system resolution enhancement are introduced. Finally, the development trends of infrared image processing are also presented.

参考文献

[1] 冯涛, 金伟其, 司俊杰. 非制冷红外焦平面探测器及其技术发展动态[J].红外技术, 2015, 37(3): 177-184.

FENG Tao, JING Weiqi, SI Junjie. Uncooled infrared FPA-A review and forecast[J]. Infrared Technology, 2015, 37(3): 177-184.

[2] 曹扬, 金伟其, 刘崇亮, 等. 红外焦平面阵列的自适应非均匀性校正及硬件实现[J]. 光学精密工程, 2011, 19(12): 2985-2991.

CAO Yang, JING Weiqi, LIU Chongliang, et al. Adaptive nonuniformity correction and hardware implementation of IRFPA[J]. Optics and Precision Engineering, 2011, 19(12): 2985-2991.

[3] 潘科辰. 基于国产红外焦平面阵列的非均匀性校正技术研究[D]. 南京:南京理工大学, 2016.

PAN Kechen. Research on the nonuniformity correction technology based on demestic IRFPA detector[D]. Nanjing: Nanjing University of Science and Technology, 2016.

[4] ZUO C, CHEN Q, GU G, et al. New temporal high-pass filter nonuniformity correction based on bilateral filter[J]. Optical Review, 2011, 18(2): 197-202.

[5] 陈芳林, 张宝辉, 汪贵华, 等. 改进的神经网络非均匀性校正算法研究[J]. 科学技术与工程, 2016, 16(33): 215-220.

CHEN Fanglin, ZHANG Baohui, WANG Guihua, et al. Research on the nonuniformity correction based on improved neural net algorithm[J]. Science and Technology and Engineering, 2016, 16(33): 215-220.

[6] 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, 2011, 28(6):1164-76.

[7] XU Honglie, CHEN Qian, SUI Xiubao, et al. Space projection estimator and temporal iteration scene-based non-uniformity correction algorithm[J]. J. Infrared Millim. Waves, 2015, 34(6): 710-714.

[8] Bae Y, Ra J B. Scene-based nonuniformity correction in infrared videos[C]//Proc. of SPIE, 2012, 8399: 14.

[9] QU H M, GONG J T, HUANG Y, et al. New Non-uniformity correction approach for infrared focal plane arrays imaging[J]. Journal of the Optical Society of Korea, 2013, 17(2): 213-218.

[10] FLIR Systems Inc. Digital detail enhancement, technical note [EB/OL]. [2013-06-12]. www.flir.com/uploadedfiles/Eurasia/MMC/Tech_Notes.

[11] Branchitta F, Diani M, Romagnoli M. New technique for the visualization of high dynamic range infrared images[J]. Optical Engineering, 2009, 48(9): 6401.

[12] ZUO C, CHEN Q, REN J. Display and detail enhancement for high-dynamic-range infrared images[J]. Optical Engineering, 2011, 50(12): 895-900.

[13] Rossi A, Acito N, Diani M, et al. High dynamic range compression for visualization of IR images in maritime scenarios[C]//Proc. of SPIE on Electro-Optical and Infrared Systems: Technology and Applications IX, 2012, 8541: 85410V.

[14] ZHANG F, XIE W, MA G, et al. High dynamic range compression and detail enhancement of infrared images in the gradient domain[J]. Infrared Physics & Technology, 2014, 67: 441-454.

[15] Frederic Garcia, Cedric Schockaert, Bruno Mirbach. Media-real-time visualization of low contrast targets from high-dynamic-range infrared images based on temporal digital detail enhancement filter[J]. Journal of Electronic Imaging, 2015, 24(6): 061103.

[16] FAN Z, BI D, GAO S, et al. Adaptive enhancement for infrared image using shearlet frame[J]. Journal of Optics, 2016, 18(8): 085706.

[17] 白俊奇, 陈钱, 屈惠明. 红外凝视成像光学微扫描重建技术研究[J]. 红外与毫米波学报, 2008, 27(4): 257-260.

BAI Junqi, CHEN Qian, QU Huiming. Research on optical micros caning reconstruction for infrared staring imaging[J]. J. Infrared Millim. Waves, 2008, 27(4): 257-260.

[18] 隋修宝, 陈钱, 陆红红. 红外图像空间分辨率提高方法研究[J]. 红外与毫米波学报, 2007, 26(5): 377-385.

SUI Xiubao, CHEN Qian, LU Honghong. Research on improving spatial resolution of infrared image[J]. J. Infrared Millim. Waves, 2007, 26(5): 377-385.

[19] SUN Mingjie, YU Kanglong. Effect of pixel active area shapes on microscanning based infrared super-resolution imaging [J]. Infrared and Laser Engineering, 2015, 44(1): 48-52.

[20] 范宏波. 基于1152×6 长波线列探测器的高性能红外搜索预警系统[J]. 红外技术, 2010, 32(1): 20-24.

FAN Hongbo. A high performance IRST system based on 1152×6 LWIR detectors[J]. Infrared Technology, 2010, 32(1): 20-24.

[21] KATIE SHEA. HGH Infrared Systems news. Debut of Spynel-S [EB/OL]. [2013-04-18]. https: //www.hgh-infrared.com/ News/News/ Debut-of-Spynel-S.

[22] Elbit Systems. Infrared Wide Area Persistent Surveillance System [EB/OL]. [2016-08-06]. http: //elbitsystems. com/pr-new/elbit-systems -introduces -supervisir/.

张宝辉, 姚立斌, 张巍伟, 陈莹妍, 王润宇. 红外图像校正与增强技术研究现状[J]. 红外技术, 2017, 39(6): 481. ZHANG Baohui, YAO Libin, ZHANG Weiwei, CHEN Yingyan, WANG Runyu. The Current Research Status of Infrared Image Correction and Enhancement[J]. Infrared Technology, 2017, 39(6): 481.

红外图像校正与增强技术研究现状

关于本站 Cookie 的使用提示

全站搜索

红外图像校正与增强技术研究现状

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索