[1] 于俊庭, 李少毅, 张平, 等. 光电成像末制导智能化技术研究与展望 [J]. 红外与激光工程, 2023, 52(05): 249-64.
YU J T, LI S Y, ZHANG P, et al. Research and prospect of intelligent technology of optoelectronic imaging termi-nal guidance [J]. Infrared and Laser Engineering, 2023, 52(05): 249-64 (in Chinese)
[2] 赵善彪, 张天孝, 李晓钟. 红外导引头综述 [J]. 飞航导弹, 2006, (08): 42-5.
ZHAO S B, ZHANG T X, LI X Z. Overview of infrared seekers [J]. Aerodynamic Missile Journal, 2006, (08): 42-5 (in Chinese).
[3] 赵志刚, 王鑫, 彭廷海, 等. 国外中长波双波段红外成像技术的发展及应用 [J]. 红外技术, 2020, 42(04): 312-9.
ZHAO Z G, WANG X, PENG T H, et al. Status Quo and Application of Middle and Long Wave Dual-band In-frared Imaging Technologies in Occident [J]. Infrared Technology, 2020, 42(04): 312-9 (in Chinese).
[4] 张兴德, 李荣刚, 刘琳, 等. 红外双波段成像系统的研究与发展 [J]. 激光与红外, 2010, 40(08): 801-4.
ZHANG X D, LI R G, LIU L, et al. Research and devel-opment of dual-band infrared camera system. [J]. Laser & Infrared, 2010, 40(08): 801-4 (in Chinese).
[5] 贾明东, 李根, 贺仕伟, 等. 双波段红外目标检测综述 [J]. 飞控与探测, 2023, 6(02): 60-9.
JIA D M, LI G, HE S W, et al. Review of Two-Band Infrared Target Detection [J]. Flight Control & Detection, 2023, 6(02): 60-9 (in Chinese).
[6] LIU Y, CHEN X, WANG Z, et al. Deep learning for pixel-level image fusion: Recent advances and future prospects [J]. Information Fusion, 2018, 42: 158-73.
[7] 李泽军, 李志勇, 占明明, 等. 光谱型红外诱饵剂研究进展 [J]. 固体火箭技术: 1-9.
LI Z J, LI Z Y, ZHAN M M, et al. Research progress of spectral improved infrared decoy [J]. Journal of Solid Rocket Technology: 1-9 (in Chinese).
[8] 黄猛, 王雅芬, 沙江, 等. 美国近年发展的红外末制导反舰导弹综述[C]//第十五届全国信号和智能信息处理与应用学术会议论文集. 重庆, 2022: 4.
HUANG M, WANG Y F, SHA J, et al. Summary of Infrared Terminally Guided Anti-ship Missiles Devel-oped by United States in Recent Years[C]// Proceedings of the 15th National Conference on Signal and Intelligent Information Processing and Application. Chongqing, 2022: 4 (in Chinese).
[9] 吕洁, 罗勇, 卿松, 等. 红外制导技术在空空导弹中的应用分析 [J]. 兵器装备工程学报, 2017, 38(12): 70-4.
LV J, LUO Y, QING S, et al. Application Analysis of Infrared Guidance Technology in Air-to-Air Missile [J]. Journal of Ordnance Equipment Engineering, 2017, 38(12): 70-4 (in Chinese).
[10] LEE D D, SEUNG H S. Learning the parts of objects by non-negative matrix factorization [J]. Nature, 1999, 401(6755): 788-91.
[11] STEELE P M, PERCONTI P. Part task investigation of multispectral image fusion using gray scale and synthetic color night vision sensor imagery for helicopter pilotage; proceedings of the Targets and Backgrounds: Characteri-zation and Representation III, F, 1997 [C]. SPIE.
[12] 吴少迟. 基于FPGA的双波段红外图像融合实时处理系统 [D]. 南京: 南京理工大学, 2018.
WU S C. Dual-band infrared image fusion real-time processing system based on FPGA [D]. Nanjing: Nan-jing University of Science and Technology, 2018 (in Chinese).
[13] MüLLER M, SCHREER O, SáENZ M L. Real-time image processing and fusion for a new high-speed dual-band infrared camera; proceedings of the Infrared Imag-ing Systems: Design, Analysis, Modeling, and Testing XVIII, F, 2007 [C]. SPIE.
[14] 赵玲, 周宽, 喻松林, 等. DRF红外双波段彩色图像融合算法 [J]. 激光与红外, 2022, 52(01): 64-70.
ZHAO L, ZHOU K, YU S L, et al. DRF infrared dual color image fusion algorithm [J]. Laser & Infrared, 2022, 52(01): 64-70 (in China).
[15] 赵玲. 基于红外双波段的图像融合技术研究 [D]. 北京: 中国电子科技集团公司电子科技研究院, 2022.
ZHAO L. Based on Infrared Dual-Band Image Fusion Technology [D]. Beijing: China Academic of Electronics and Information Technology, 2022 (in China).
[16] 罗璐瑶. 双色红外图像融合处理技术研究及实现 [D]. 南京: 南京理工大学, 2020.
LUO L Y. Research and implementation of two-color infrared image fusion processing technology [D]. Nan-jing: Nanjing University of Science and Technology, 2020 (in Chinese).
[17] BURT P J, ADELSON E H. The Laplacian pyramid as a compact image code [M]. Readings in computer vision. Elsevier. 1987: 671-9.
[18] TOET A, VAN RUYVEN L J, VALETON J M. Merg-ing thermal and visual images by a contrast pyramid [J]. Optical engineering, 1989, 28(7): 789-92.
[19] TOET A. A morphological pyramidal image decomposi-tion [J]. Pattern recognition letters, 1989, 9(4): 255-61.
[20] MARSHALL S, MATSOPOULOS G K, BRUNT J N. Fusion of MR and CT images of the human brain using multiresolution morphology [J]. Mathematical morphol-ogy and its applications to image processing, 1994: 317-24.
[21] PETROVIC V S, XYDEAS C S. Gradient-based multi-resolution image fusion [J]. IEEE Transactions on Image processing, 2004, 13(2): 228-37.
[22] KARALI A O, CAKIR S, AYTA? T. Multiscale contrast direction adaptive image fusion technique for MWIR-LWIR image pairs and LWIR multifocus infrared images [J]. Applied Optics, 2015, 54(13): 4172-9.
[23] 陈力. 双波段图像融合方法研究 [D]. 南京: 南京理工大学, 2016.
CHEN L. Research on dual-band image fusion method [D] . Nanjing: Nanjing University of Science and Tech-nology, 2016 (in Chinese).
[24] 朱亮亮. 红外融合方法及测试技术研究 [D]. 南京: 南京理工大学, 2021.
ZHU L L. Research on infrared fusion method and test-ing technology [D]. Nanjing: Nanjing University of Sci-ence and Technology, 2021 (in Chinese).
[25] LI H, MANJUNATH B, MITRA S K. Multisensor im-age fusion using the wavelet transform [J]. Graphical models and image processing, 1995, 57(3): 235-45.
[26] MALLAT S G. Multifrequency channel decompositions of images and wavelet models [J]. IEEE Transactions on Acoustics, speech, and signal processing, 1989, 37(12): 2091-110.
[27] 孙玉秋, 田金文, 柳健. 基于小波变换的双色红外图像融合检测方法 [J]. 红外与激光工程, 2007, (02): 240-3.
SUN Y Q, TIAN J W, LIU J. Dual band infrared image fusion detection based on wavelet transform [J]. Infrared and Laser Engineering, 2007, (02): 240-3 (in Chinese).
[28] 朱祥玲, 吴钦章, 陈洪. 基于小波变换的双波段红外图像融合方法 [J]. 激光与红外, 2014, 44(05): 572-6.
ZHU X L, WU Q Z, CHEN H. Fusion algorithm of dual waveband infrared image based on wavelet transfor-mation [J]. Laser & Infrared, 2014, 44(05): 572-6 (in Chinese).
[29] 付莹. 海面双波段红外图像配准与融合方法研究 [D]. 大连: 大连海事大学, 2017.
FU Y. Research on Registration and Fusion Methods of Dual-band Infrared Image of Sea Surface [D]. Da-lian: Dalian Maritime University, 2017 (in Chinese).
[30] 仇荣超, 吕俊伟, 宫剑, 等. 多波段前视红外图像融合的海面杂乱背景平滑方法 [J]. 光谱学与光谱分析, 2020, 40(04): 1120-6.
QIU R C, LV J W, GONG J, et al. Smoothing Method for Sea Surface Rough Background Based on Multi-Spectral Forward-Looking Infrared Image Fusion [J]. Spectroscopy and Spectral Analysis, 2020, 40(04): 1120-6 (in Chinese).
[31] 张承泓. 红外双波段图像融合系统关键技术研究 [D]. 北京: 中国科学院大学, 2017.
ZHANG C H. Research on Key Technologies of Dual Band Infrared Image Fusion System [D]. Beijing: Uni-versity of Chinese Academy of Sciences, 2017 (in Chi-nese).
[32] 陈皓. 双波段红外成像及数据融合技术研究 [D]. 北京: 中国科学院大学, 2014.
CHEN H. Research for Dual-band Infrared Imagery and Date Fusion [D] . Beijing: University of Chinese Academy of Sciences, 2014 (in Chinese).
[33] JOHNSON J L, PADGETT M L. PCNN models and applications [J]. IEEE transactions on neural networks, 1999, 10(3): 480-98.
[34] 李华锋. 非采样Contourlet变换与PCNN相结合的图像融合方法研究 [D]. 重庆: 重庆大学, 2009.
LI H F. Study on the Method of Image Fusion Based on Nonsubsampled Contourlet Transform and PCNN [D]. Chongqing: ChongqingUniversity, 2009 (in Chinese).
[35] 祝念. 高温尾焰红外光谱特性分析及探测波段选取技术研究 [D]. 北京: 中国科学院大学, 2018.
ZHU N. Analysis of Infrared Spectra Characteristics of High Temperature Plume and Selection of Detection Bands [D]. Beijing: University of Chinese Academy of Sciences, 2018 (in Chinese).
[36] 马振华. 基于双波段的红外目标探测算法研究 [D]. 西安: 西安电子科技大学, 2018.
MA Z H. The Research on Dual-band Infrared Tar-get Detection Algorithm [D]. Xi’an: Xidian University, 2018 (in Chinese).
[37] MIAO Q-G, SHI C, XU P-F, et al. A novel algorithm of image fusion using shearlets [J]. Optics Communications, 2011, 284(6): 1540-7.
[38] 陈堃. 基于红外双波段的图像融合技术研究 [D]. 西安: 西安电子科技大学, 2019.
CHEN K. Research on Infrared Dual-Band Image Fu-sion Technology [D]. Xi’an: Xidian University, 2019 (in Chinese).
[39] YANG B, LI S. Pixel-level image fusion with simultane-ous orthogonal matching pursuit [J]. Information fusion, 2012, 13(1): 10-9.
[40] MAIRAL J, BACH F, PONCE J, et al. Online learning for matrix factorization and sparse coding [J]. Journal of Machine Learning Research, 2010, 11(1).
[41] YANG B, LI S. Multifocus image fusion and restoration with sparse representation [J]. IEEE transactions on In-strumentation and Measurement, 2009, 59(4): 884-92.
[42] YU N, QIU T, BI F, et al. Image features extraction and fusion based on joint sparse representation [J]. IEEE Journal of selected topics in signal processing, 2011, 5(5): 1074-82.
[43] YIN H, LI S, FANG L. Simultaneous image fusion and super-resolution using sparse representation [J]. Infor-mation Fusion, 2013, 14(3): 229-40.
[44] 李美丽, 李言俊, 王红梅, 等. NSCT和非负矩阵分解的图像融合方法 [J]. 计算机工程与应用, 2010, 46(08): 21-4.
LI M L, Li Y J, W H M, et al. Image fusion algorithm based on NSCT and non-negative matrix factorization [J]. Computer Engineering and Applications, 2010, 46(08): 21-4 (in Chinese).
[45] LIU Y, LIU S, WANG Z. A general framework for im-age fusion based on multi-scale transform and sparse representation [J]. Information fusion, 2015, 24: 147-64.
[46] 李朝阳. 红外多波段图像融合算法研究 [D]. 北京: 中国科学院大学, 2018.
LI Z Y. Research on multi band infrared image fusion algorithm [D]. Beijing: University of Chinese Academy of Sciences, 2018 (in Chinese).
[47] ZHENG Y, ESSOCK E A, HANSEN B C. An advanced image fusion algorithm based on wavelet transform: in-corporation with PCA and morphological processing; proceedings of the Image processing: algorithms and systems III, F, 2004 [C]. SPIE.
[48] ZHENG Y, ESSOCK E A, HANSEN B C, et al. A new metric based on extended spatial frequency and its appli-cation to DWT based fusion algorithms [J]. Information Fusion, 2007, 8(2): 177-92.
[49] QINGWANG Q, KUN G, GUOQIANG N. Image Fu-sion and Its Real-time Processing in Dual-band Infrared Night Vision System; proceedings of the Proc of SPIE Vol, F, 2009 [C].
[50] ZHANG Y, LIU Y, SUN P, et al. IFCNN: A general image fusion framework based on convolutional neural network [J]. Information Fusion, 2020, 54: 99-118.
[51] 冯迪. 基于深度学习的红外双波段图像融合算法研究 [D]. 武汉: 华中科技大学, 2021.
FENG D. A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Engineer-ing [D]. Wuhan: Huazhong University of Science and Technology, 2021 (in Chinese).
[52] 王宇. 长线列红外中长波图像融合关键技术研究 [D]. 北京: 中国科学院大学, 2014.
WANG Y. Research on Key Technologies for Long Lin-ear Mid-wave and Long-wave IR Image Fusion [D]. Beijing: University of Chinese Academy of Sciences, 2018 (in Chinese).
[53] GOODFELLOW I, POUGET-ABADIE J, MIRZA M, et al. Generative adversarial nets [J]. Advances in neural information processing systems, 2014, 27.
[54] RADFORD A, METZ L, CHINTALA S. Unsupervised representation learning with deep convolutional genera-tive adversarial networks [J]. arXiv preprint arXiv:151106434, 2015.
[55] MA J, MA Y, LI C. Infrared and visible image fusion methods and applications: A survey [J]. Information fu-sion, 2019, 45: 153-78.
[56] DESHPANDE S D, ER M H, VENKATESWARLU R, et al. Max-mean and max-median filters for detection of small targets; proceedings of the Signal and Data Pro-cessing of Small Targets 1999, F, 1999 [C]. SPIE.
[57] AGHAZIYARATI S, MORADI S, TALEBI H. Small infrared target detection using absolute average difference weighted by cumulative directional derivatives [J]. Infra-red Physics & Technology, 2019, 101: 78-87.
[58] MORADI S, MOALLEM P, SABAHI M F. Fast and robust small infrared target detection using absolute di-rectional mean difference algorithm [J]. Signal Pro-cessing, 2020, 177: 107727.
[59] CHEN C P, LI H, WEI Y, et al. A local contrast method for small infrared target detection [J]. IEEE transactions on geoscience and remote sensing, 2013, 52(1): 574-81.
[60] HAN J, MA Y, ZHOU B, et al. A robust infrared small target detection algorithm based on human visual system [J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(12): 2168-72.
[61] WEI Y, YOU X, LI H. Multiscale patch-based contrast measure for small infrared target detection [J]. Pattern Recognition, 2016, 58: 216-26.
[62] WANG H, ZHOU L, WANG L. Miss detection vs. false alarm: Adversarial learning for small object segmentation in infrared images; proceedings of the Proceedings of the IEEE/CVF International Conference on Computer Vision, F, 2019 [C].
[63] ZHAO M, CHENG L, YANG X, et al. TBC-Net: A real-time detector for infrared small target detection using se-mantic constraint [J]. arXiv preprint arXiv:200105852, 2019.
[64] LI B, XIAO C, WANG L, et al. Dense nested attention network for infrared small target detection [J]. IEEE Transactions on Image Processing, 2022, 32: 1745-58.
[65] ZHANG T, LI L, CAO S, et al. Attention-guided pyra-mid context networks for detecting infrared small target under complex background [J]. IEEE Transactions on Aerospace and Electronic Systems, 2023.
[66] 黄浩. 双波段红外成像目标检测与识别方法研究 [D]. 长沙: 国防科技大学, 2013.
HUANG H. Research on Techniques of Detection and Recognition of Target in Dual-band Infrared [D]. Chang-sha: National University of Defense Technology, 2013 (in Chinese).
[67] 李秋华. 双色红外成像制导自动目标识别与跟踪技术研究 [D]. 长沙: 国防科技大学, 2008.
LI Q H. Automatic Target Recognition and Tracking Technology for the Two-Color IR Imaging Guidence [D]. Changsha: National University of Defense Technology, 2008 (in Chinese).
[68] 黄浩, 陶华敏, 陈尚锋. 基于混合融合策略的双波段红外小目标检测方法 [J]. 红外与激光工程, 2014, 43(09): 2827-31.
HUANG H, TAO H M, CHEN S F. Dual-band infrared dim target detection based on hybrid fusion algorithm [J]. Infrared and Laser Engineering, 2014, 43(09): 2827-31 (in Chinese). |