Shutter-less Non-uniformity Correction Methods in Uncooled Infrared Imagery

HUANG Yuanfei; HUANG Hua

doi:10.11999/JEIT231400

Volume 46 Issue 5

May 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(5): 2198-2216

HUANG Yuanfei, HUANG Hua. Shutter-less Non-uniformity Correction Methods in Uncooled Infrared Imagery[J]. Journal of Electronics & Information Technology, 2024, 46(5): 2198-2216. doi: 10.11999/JEIT231400

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HUANG Yuanfei, HUANG Hua. Shutter-less Non-uniformity Correction Methods in Uncooled Infrared Imagery[J]. Journal of Electronics & Information Technology, 2024, 46(5): 2198-2216. doi: 10.11999/JEIT231400

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Shutter-less Non-uniformity Correction Methods in Uncooled Infrared Imagery

doi: 10.11999/JEIT231400

HUANG Yuanfei,
HUANG Hua^,

School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China

Funds: The National Natural Science Foundation of China (62202056)

Received Date: 2023-12-19
Rev Recd Date: 2024-05-11

Available Online: 2024-05-13

Publish Date: 2024-05-30

Abstract

Abstract

Due to the limitations of imaging principles and processing technology, uncooled infrared imagery detectors suffer from serious non-uniformities, damaging the imaging results. To improve the quality of infrared images, non-uniformity correction techniques are of great significance for practical applications. According to the physical formation and spatial characteristics of the non-uniformity in uncooled infrared imagery detectors, this paper divides these common non-uniformities into three categories: low-frequency non-uniformity, shot non-uniformity, and stripe non-uniformity. The physical mechanisms of these non-uniformities are further explored from the procedure in the optical system, thermal materials, and amplifier circuit of the uncooled infrared imagery detector. Then, the existing shutter-less non-uniformity correction methods are systematically summarized. Based on the principles of the methods, statistical-based, filter-based, optimization-based, and learning-based non-uniformity correction methods are categorized. Besides, the specifics of each method in dealing with different non-uniformities are clarified and distinguished. Finally, the existing problems in the current methods are reviewed and summarized, and the development trend of non-uniformity correction methods in future practical applications is prospected.
- Uncooled infrared imagery,
- Non-uniformity correction,
- Imaging mechanism,
- Image denoising

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References(102)

References

[1]	刘靳, 姬红兵. 基于非平稳背景下的红外小目标检测[J]. 电子与信息学报, 2010, 32(6): 1295–1300. doi: 10.3724/SP.J.1146.2009.01083. LIU Jin and JI Hongbing. IR small targets detection based on non-homogeneous background[J]. Journal of Electronics & Information Technology, 2010, 32(6): 1295–1300. doi: 10.3724/SP.J.1146.2009.01083.
[2]	余黎静, 唐利斌, 杨文运, 等. 非制冷红外探测器研究进展(特邀)[J]. 红外与激光工程, 2021, 50(1): 20211013. doi: 10.3788/IRLA20211013. YU Lijing, TANG Libin, YANG Wenyun, et al. Research progress of uncooled infrared detectors (Invited)[J]. Infrared and Laser Engineering, 2021, 50(1): 20211013. doi: 10.3788/IRLA20211013.
[3]	HE Zewei, CAO Yanpeng, DONG Yafei, et al. Single-image-based nonuniformity correction of uncooled long-wave infrared detectors: A deep-learning approach[J]. Applied Optics, 2018, 57(18): D155–D164. doi: 10.1364/AO.57.00D155.
[4]	姚婷, 梁成文, 李凯扬. 探测器温度对非制冷红外热像仪人体测温的影响与修正[J]. 红外技术, 2016, 38(11): 984–989. YAO Ting, LIANG Chengwen, and LI Kaiyang. Effect of detector temperature on the human body temperature measurement of uncooled infrared thermal imager and its correction[J]. Infrared Technology, 2016, 38(11): 984–989.
[5]	JIN Yan, JIANG Jie, and ZHANG Guangjun. Three-step nonuniformity correction for a highly dynamic intensified charge-coupled device star sensor[J]. Optics Communications, 2012, 285(7): 1753–1758. doi: 10.1016/j.optcom.2011.12.043.
[6]	CHANG Songtao and LI Zhou. Single-reference-based solution for two-point nonuniformity correction of infrared focal plane arrays[J]. Infrared Physics & Technology, 2019, 101: 96–104. doi: 10.1016/j.infrared.2019.06.007.
[7]	王成龙, 王春阳, 谷健, 等. 一种基于定标的非均匀性校正改进算法[J]. 中国光学, 2022, 15(3): 498–507. doi: 10.37188/CO.2021-0231. WANG Chenglong, WANG Chunyang, GU Jian, et al. An improved non-uniformity correction algorithm based on calibration[J]. Chinese Optics, 2022, 15(3): 498–507. doi: 10.37188/CO.2021-0231.
[8]	ZUO Chao, CHEN Qian, GU Guohua, et al. Scene-based nonuniformity correction algorithm based on interframe registration[J]. Journal of the Optical Society of America A, 2011, 28(6): 1164–1176. doi: 10.1364/JOSAA.28.001164.
[9]	RONG Shenghui, ZHOU Huixin, ZHAO Dong, et al. Infrared fix pattern noise reduction method based on shearlet transform[J]. Infrared Physics & Technology, 2018, 91: 243–249. doi: 10.1016/j.infrared.2018.05.002.
[10]	CAO Yanpeng, HE Zewei, YANG Jiangxin, et al. Spatially adaptive column fixed-pattern noise correction in infrared imaging system using 1d horizontal differential statistics[J]. IEEE Photonics Journal, 2017, 9(5): 1–13. doi: 10.1109/JPHOT.2017.2752000.
[11]	SONG Lingfei and HUANG Hua. Spatial and temporal adaptive nonuniformity correction for infrared focal plane arrays[J]. Optics Express, 2022, 30(25): 44681–44700. doi: 10.1364/OE.471825.
[12]	LIU Tong, SUI Xiubao, WANG Yihong, et al. Strong non-uniformity correction algorithm based on spectral shaping statistics and LMS[J]. Optics Express, 2023, 31(19): 30693–30709. doi: 10.1364/OE.496398.
[13]	GOYAL P. Review of infrared signal processing algorithms[J]. International Journal of Computer Science and Technology, 2011, 2(2): 176–180.
[14]	WANMALI S and SHEKOKAR R. Survey on some scene based nonuniformity correction algorithms for infrared images[J]. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Co/*10.17148/IJIREEICE. 2017.5421.
[15]	董立泉, 金伟其, 隋婧. 基于场景的红外焦平面阵列非均匀性校正算法综述[J]. 光学技术, 2008, 34(S1): 112–118. doi: 10.13741/j.cnki.11-1879/o4.2008.s1.068. DONG Liquan, JIN Weiqi, and SUI Jing. Study on the scene-based non-unifonnitV correction algorithms for IRFPA[J]. Optical Technique, 2008, 34(S1): 112–118. doi: 10.13741/j.cnki.11-1879/o4.2008.s1.068.
[16]	YU Yuan, LEE B G, PIKE M, et al. Deep learning-based RGB-thermal image denoising: Review and applications[J]. Multimedia Tools and Applications, 2024, 83(4): 11643–11641. doi: 10.1007/s11042-023-15916-7.
[17]	刘子骥. 非制冷红外焦平面探测器测试及验证成像技术研究[D]. [博士论文], 电子科技大学, 2013. LIU Ziji. Study on uncooled infrared focal plane detector testing and imaging technology[D]. [Ph. D. dissertation], University of Electronic Science and Technology of China, 2013.
[18]	LI Yiyang, JIN Weiqi, and LIU Zhihao. Interior radiation noise reduction method based on multiframe processing in infrared focal plane arrays imaging system[J]. IEEE Photonics Journal, 2018, 10(5): 1–12. doi: 10.1109/JPHOT.2018.2865224.
[19]	王帅, 赵耀宏, 向伟. 单帧红外图像低频非均匀性噪声校正算法[J]. 计算机辅助设计与图形学学报, 2020, 32(5): 811–819. doi: 10.3724/SP.J.1089.2020.17890. WANG Shuai, ZHAO Yaohong, and XIANG Wei. Single image based nonuniformity correction method in infrared camera[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(5): 811–819. doi: 10.3724/SP.J.1089.2020.17890.
[20]	MAGGIONI M, SÁNCHEZ-MONGE E, and FOI A. Joint removal of random and fixed-pattern noise through spatiotemporal video filtering[J]. IEEE Transactions on Image Processing, 2014, 23(10): 4282–4296. doi: 10.1109/TIP.2014.2345261.
[21]	SONG Lingfei and HUANG Hua. Fixed pattern noise removal based on a semi-calibration method[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(10): 11842–11855. doi: 10.1109/TPAMI.2023.3274826.
[22]	CHANG Yi, YAN Luxin, WU Tao, et al. Remote sensing image stripe noise removal: From image decomposition perspective[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(12): 7018–7031. doi: 10.1109/TGRS.2016.2594080.
[23]	SONG Lingfei and HUANG Hua. Simultaneous destriping and image denoising using a nonparametric model with the EM algorithm[J]. IEEE Transactions on Image Processing, 2023, 32: 1065–1077. doi: 10.1109/TIP.2023.3239193.
[24]	史浩然, 沈同圣, 李召龙, 等. 红外系统中渐晕效应的模拟方法研究[J]. 红外技术, 2015, 37(4): 296–299. SHI Haoran, SHEN Tongsheng, LI Zhaolong, et al. Simulation of the vignetting effect in infrared imaging system[J]. Infrared Technology, 2015, 37(4): 296–299.
[25]	WU Zimu and WANG Xia. Non-uniformity correction for medium wave infrared focal plane array-based compressive imaging[J]. Optics Express, 2020, 28(6): 8541–8559. doi: 10.1364/OE.381523.
[26]	KUANG Xiaodong, SUI Xiubao, LIU Yuan, et al. Single infrared image optical noise removal using a deep convolutional neural network[J]. IEEE Photonics Journal, 2018, 10(2): 7800615. doi: 10.1109/JPHOT.2017.2779149.
[27]	隋修宝. 非制冷凝视热像仪成像理论以及关键技术研究[D]. [博士论文], 南京理工大学, 2009. SUI Xiubao. Research on the imaging theory and the key techniques of uncooled staring thermal imager[D]. [Ph. D. dissertation]. Nanjing University of Science and Technology, 2009.
[28]	ABDEL-RAHMAN M, ILAHI S, ZIA M F, et al. Temperature coefficient of resistance and thermal conductivity of Vanadium oxide ‘Big Mac’ sandwich structure[J]. Infrared Physics & Technology, 2015, 71: 127–130. doi: 10.1016/j.infrared.2015.03.006.
[29]	GENG Lixiang, CHEN Qian, and QIAN Weixian. An adjacent differential statistics method for IRFPA nonuniformity correction[J]. IEEE Photonics Journal, 2013, 5(6): 6801615. doi: 10.1109/JPHOT.2013.2293614.
[30]	CAO Yanpeng and LI Yiqun. Strip non-uniformity correction in uncooled long-wave infrared focal plane array based on noise source characterization[J]. Optics Communications, 2015, 339: 236–242. doi: 10.1016/j.optcom.2014.10.041.
[31]	CAO Yanpeng and TISSE C L. Single-image-based solution for optics temperature-dependent nonuniformity correction in an uncooled long-wave infrared camera[J]. Optics Letters, 2014, 39(3): 646–648. doi: 10.1364/OL.39.000646.
[32]	TINCHER M, MEYER C R, GUPTA R, et al. Polynomial modeling and reduction of RF body coil spatial inhomogeneity in MRI[J]. IEEE Transactions on Medical Imaging, 1993, 12(2): 361–365. doi: 10.1109/42.232267.
[33]	LIEW A W C and YAN Hong. An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation[J]. IEEE Transactions on Medical Imaging, 2003, 22(9): 1063–1075. doi: 10.1109/TMI.2003.816956.
[34]	SRIPRAGASH L and SUNDARESAN M. Non-uniformity correction and sound zone detection in pulse thermographic nondestructive evaluation[J]. NDT & E International, 2017, 87: 60–67. doi: 10.1016/j.ndteint.2017.01.006.
[35]	TASDIZEN T, JURRUS E, and WHITAKER R T. Non-uniform illumination correction in transmission electron microscopy[C]. MICCAI Workshop on Microscopic Image Analysis with Applications in Biology, New York, USA, 2008: 5–6.
[36]	GARCÍA-SEBASTIÁN M, FERNÁNDEZ E, GRAÑA M, et al. A parametric gradient descent MRI intensity inhomogeneity correction algorithm[J]. Pattern Recognition Letters, 2007, 28(13): 1657–1666. doi: 10.1016/j.patrec.2007.04.016.
[37]	SHI Yu, CHEN Jisong, HONG Hanyu, et al. Multi-scale thermal radiation effects correction via a fast surface fitting with Chebyshev polynomials[J]. Applied Optics, 2022, 61(25): 7498–7507. doi: 10.1364/AO.465157.
[38]	HONG Hanyu, LIU Jiakang, SHI Yu, et al. Progressive nonuniformity correction for aero-optical thermal radiation images via bilateral filtering and bézier surface fitting[J]. IEEE Photonics Journal, 2023, 15(2): 7800611. doi: 10.1109/JPHOT.2023.3250949.
[39]	HARRIS J G and CHIANG Y M. Nonuniformity correction of infrared image sequences using the constant-statistics constraint[J]. IEEE Transactions on Image Processing, 1999, 8(8): 1148–1151. doi: 10.1109/83.777098.
[40]	ZHANG Chao and ZHAO Wenyi. Scene-based nonuniformity correction using local constant statistics[J]. Journal of the Optical Society of America A, 2008, 25(6): 1444–1453. doi: 10.1364/JOSAA.25.001444.
[41]	REDLICH R, FIGUEROA M, TORRES S N, et al. Embedded nonuniformity correction in infrared focal plane arrays using the constant range algorithm[J]. Infrared Physics & Technology, 2015, 69: 164–173. doi: 10.1016/j.infrared.2015.01.026.
[42]	QIAN Weixian, CHEN Qian, and GU Guohua. The high-frequency constant-statistics constraint nonuniformity correction algorithm[J]. Journal of Infrared, Millimeter, and Terahertz Waves, 2011, 32(6): 778–792. doi: 10.1007/s10762-011-9793-6.
[43]	LIU Chengwei, SUI Xiubao, LIU Yuan, et al. FPN estimation based nonuniformity correction for infrared imaging system[J]. Infrared Physics & Technology, 2019, 96: 22–29. doi: 10.1016/j.infrared.2018.09.025.
[44]	PIPA D R, DA SILVA E A B, PAGLIARI C L, et al. Recursive algorithms for bias and gain nonuniformity correction in infrared videos[J]. IEEE Transactions on Image Processing, 2012, 21(12): 4758–4769. doi: 10.1109/TIP.2012.2218820.
[45]	DELON J. Midway image equalization[J]. Journal of Mathematical Imaging and Vision, 2004, 21(2): 119–134. doi: 10.1023/B:JMIV.0000035178.72139.2d.
[46]	康长青, 张其林, 郑毅, 等. 基于中间均衡直方图的红外图像非均匀性校正[J]. 激光与红外, 2013, 43(11): 1240–1242. doi: 10.3969/j.issn.1001-5078.2013.11.08. KANG Changqing, ZHANG Qilin, ZHENG Yi, et al. Non uniformity correction algorithm for IR images based on midway equalization histogram[J]. Laser & Infrared, 2013, 43(11): 1240–1242. doi: 10.3969/j.issn.1001-5078.2013.11.08.
[47]	简献忠, 陆睿智, 郭强. 改进的单幅红外图像局部自适应非均匀校正[J]. 激光与红外, 2014, 44(12): 1344–1348. doi: 10.3969/j.issn.1001-5078.2014.12.011. JIAN Xianzhong, LU Ruizhi, and GUO Qiang. Modified locally adaptive non-uniformity correction algorithm for single infrared image[J]. Laser & Infrared, 2014, 44(12): 1344–1348. doi: 10.3969/j.issn.1001-5078.2014.12.011.
[48]	GADALLAH F L, CSILLAG F, and SMITH E J M. Destriping multisensor imagery with moment matching[J]. International Journal of Remote Sensing, 2000, 21(12): 2505–2511. doi: 10.1080/01431160050030592.
[49]	CHEN Jinsong, SHAO Yun, GUO Huadong, et al. Destriping CMODIS data by power filtering[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(9): 2119–2124. doi: 10.1109/TGRS.2003.817206.
[50]	KANG Yifei, PAN Li, SUN Mingwei, et al. Destriping high-resolution satellite imagery by improved moment matching[J]. International Journal of Remote Sensing, 2017, 38(22): 6346–6365. doi: 10.1080/01431161.2017.1353162.
[51]	韩玲, 董连凤, 张敏, 等. 基于改进的矩匹配方法高光谱影像条带噪声滤波技术[J]. 光学学报, 2009, 29(12): 3333–3338. doi: 10.3788/AOS20092912.3333. HAN Ling, DONG Lianfeng, ZHANG Min, et al. Destriping hyperspectral image based on an improved moment matching method[J]. Acta Optica Sinica, 2009, 29(12): 3333–3338. doi: 10.3788/AOS20092912.3333.
[52]	FARBMAN Z, FATTAL R, LISCHINSKI D, et al. Edge-preserving decompositions for multi-scale tone and detail manipulation[J]. ACM Transactions on Graphics, 2008, 27(3): 1–10. doi: 10.1145/1360612.1360666.
[53]	蔡秀梅, 马今璐, 吴成茂, 等. 基于模糊同态滤波的彩色图像增强算法[J]. 计算机仿真, 2020, 37(6): 342–346. doi: 10.3969/j.issn.1006-9348.2020.06.070. CAI Xiumei, MA Jinlu, WU Chengmao, et al. Color image enhancement algorithm based on fuzzy homomorphic filtering[J]. Computer Simulation, 2020, 37(6): 342–346. doi: 10.3969/j.issn.1006-9348.2020.06.070.
[54]	梁琳, 何卫平, 雷蕾, 等. 光照不均图像增强方法综述[J]. 计算机应用研究, 2010, 27(5): 1625–1628. doi: 10.3969/j.issn.1001-3695.2010.05.006. LIANG Lin, HE Weiping, LEI Lei, et al. Survey on enhancement methods for non-uniform illumination image[J]. Application Research of Computers, 2010, 27(5): 1625–1628. doi: 10.3969/j.issn.1001-3695.2010.05.006.
[55]	SOLBØ S and ELTOFT T. Homomorphic wavelet-based statistical despeckling of SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(4): 711–721. doi: 10.1109/TGRS.2003.821885.
[56]	TORRES S N, HAYAT M M, ARMSTRONG E E, et al. Kalman-filtering approach for nonuniformity correction in focal plane array sensors[C]. The SPIE, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XI, Orlando, USA, 2000: 196–205. doi: 10.1117/12.391780.
[57]	ROSSI A, DIANI M, and CORSINI G. Bilateral filter-based adaptive nonuniformity correction for infrared focal-plane array systems[J]. Optical Engineering, 2010, 49(5): 057003. doi: 10.1117/1.3425660.
[58]	RONG Shenghui, ZHOU Huixin, QIN Hanlin, et al. Guided filter and adaptive learning rate based non-uniformity correction algorithm for infrared focal plane array[J]. Infrared Physics & Technology, 2016, 76: 691–697. doi: 10.1016/j.infrared.2016.04.037.
[59]	LAI Rui, YUE Gaoyu, and ZHANG Gangxuan. Total variation based neural network regression for nonuniformity correction of infrared images[J]. Symmetry, 2018, 10(5): 157. doi: 10.3390/sym10050157.
[60]	杨硕, 赵保军, 毛二可, 等. 基于PM扩散的红外焦平面阵列神经网络非均匀校正算法[J]. 电子与信息学报, 2013, 35(11): 2744–2750. doi: 10.3724/SP.J.1146.2012.01051. YANG Shuo, ZHAO Baojun, MAO Erke, et al. Neural network non-uniformity correction for infrared focal plane array based on perona malik diffusion[J]. Journal of Electronics & Information Technology, 2013, 35(11): 2744–2750. doi: 10.3724/SP.J.1146.2012.01051.
[61]	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. doi: 10.1364/OE.17.014918.
[62]	VERA E and TORRES S. Fast adaptive nonuniformity correction for infrared focal-plane array detectors[J]. EURASIP Journal on Advances in Signal Processing, 2005, 2005: 560759. doi: 10.1155/ASP.2005.1994.
[63]	GODOY S E, PEZOA J E, and TORRES S N. Noise cancellation based nonuniformity correction algorithm for infrared focal-plane arrays[J]. Applied Optics, 2008, 47(29): 5394–5399. doi: 10.1364/AO.47.005394.
[64]	ZUO Chao, CHEN Qian, GU Guohua, et al. New temporal high-pass filter nonuniformity correction based on bilateral filter[J]. Optical Review, 2011, 18(2): 197–202. doi: 10.1007/s10043-011-0042-y.
[65]	HUANG Jun, MA Yong, FAN Fan, et al. A scene-based nonuniformity correction algorithm based on fuzzy logic[J]. Optical Review, 2015, 22(4): 614–622. doi: 10.1007/s10043-015-0107-4.
[66]	MORRIS N J W, AVIDAN S, MATUSIK W, et al. Statistics of infrared images[C]. 2007 IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, USA, 2007: 1–7. doi: 10.1109/CVPR.2007.383003.
[67]	CAO Yanpeng, YANG M Y, and TISSE C L. Effective strip noise removal for low-textured infrared images based on 1-D guided filtering[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2016, 26(12): 2176–2188. doi: 10.1109/TCSVT.2015.2493443.
[68]	LIU Na, LI Wei, TAO Ran, et al. Wavelet-domain low-rank/group-sparse destriping for hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(12): 10310–10321. doi: 10.1109/TGRS.2019.2933555.
[69]	ZHENG Yuanjie, YU Jingyi, KANG S B, et al. Single-image vignetting correction using radial gradient symmetry[C]. 2008 IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, USA, 2008: 1–8. doi: 10.1109/CVPR.2008.4587413.
[70]	SHI Yu, HONG Hanyu, HUA Xia, et al. Aero-optic thermal radiation effects correction with a low-frequency prior and a sparse constraint in the gradient domain[J]. Journal of the Optical Society of America A, 2019, 36(9): 1566–1572. doi: 10.1364/JOSAA.36.001566.
[71]	LIU Li and ZHANG Tianxu. Intensity non-uniformity correction of aerothermal images via ℓ_p-regularized minimization[J]. Journal of the Optical Society of America A, 2016, 33(11): 2206–2212. doi: 10.1364/JOSAA.33.002206.
[72]	LIU Li and ZHANG Tianxu. Optics temperature-dependent nonuniformity correction via ℓ₀-regularized prior for airborne infrared imaging systems[J]. IEEE Photonics Journal, 2016, 8(5): 3900810. doi: 10.1109/JPHOT.2016.2602059.
[73]	LI Zhenhua, XU Guili, CHENG Yuehua, et al. A structure prior weighted hybrid ℓ₂-ℓ_p variational model for single infrared image intensity nonuniformity correction[J]. Optik, 2021, 229: 165867. doi: 10.1016/j.ijleo.2020.165867.
[74]	WANG Yu, WANG Yihong, LIU Tong, et al. Enhancing infrared imaging systems with temperature-dependent nonuniformity correction via single-frame and inter-frame structural similarity[J]. Applied Optics, 2023, 62(26): 7075–7082. doi: 10.1364/AO.497228.
[75]	MIAO Xinyuan, ZHANG Ye, and ZHANG Junping. Thermal hyperspectral image denoising using total variation based on bidirectional estimation and brightness temperature smoothing[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 7001205. doi: 10.1109/LGRS.2021.3066627.
[76]	WAN Minjie, GU Guohua, XU Yunkai, et al. Total variation-based interframe infrared patch-image model for small target detection[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 7003305. doi: 10.1109/LGRS.2021.3126772.
[77]	GU Shuhang, ZHANG Lei, ZUO Wangmeng, et al. Weighted nuclear norm minimization with application to image denoising[C]. 2014 IEEE Conference on Computer Vision and Pattern Recognition, Columbus, USA, 2014: 2862–2869. doi: 10.1109/CVPR.2014.366.
[78]	CHEN Yang, CAO Wenfei, PANG Li, et al. Hyperspectral image denoising via texture-preserved total variation regularizer[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5516114. doi: 10.1109/TGRS.2023.3292518.
[79]	BOUALI M and LADJAL S. Toward optimal destriping of MODIS data using a unidirectional variational model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(8): 2924–2935. doi: 10.1109/TGRS.2011.2119399.
[80]	CHANG Yi, YAN Luxin, FANG Houzhang, et al. Simultaneous destriping and denoising for remote sensing images with unidirectional total variation and sparse representation[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(6): 1051–1055. doi: 10.1109/LGRS.2013.2285124.
[81]	HE Wei, ZHANG Hongyan, ZHANG Liangpei, et al. Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(1): 178–188. doi: 10.1109/TGRS.2015.2452812.
[82]	HU Ting, LI Wei, LIU Na, et al. Hyperspectral image restoration using adaptive anisotropy total variation and nuclear norms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(2): 1516–1533. doi: 10.1109/TGRS.2020.2999634.
[83]	LIU Li, XU Luping, and FANG Houzhang. Simultaneous intensity bias estimation and stripe noise removal in infrared images using the global and local sparsity constraints[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(3): 1777–1789. doi: 10.1109/TGRS.2019.2948601.
[84]	ZHANG Kai, ZUO Wangmeng, CHEN Yunjin, et al. Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising[J]. IEEE Transactions on Image Processing, 2017, 26(7): 3142–3155. doi: 10.1109/TIP.2017.2662206.
[85]	TIAN Chunwei, FEI Lunke, ZHENG Wenxian, et al. Deep learning on image denoising: An overview[J]. Neural Networks, 2020, 131: 251–275. doi: 10.1016/j.neunet.2020.07.025.
[86]	CHANG Yi, YAN Luxin, LIU Li, et al. Infrared aerothermal nonuniform correction via deep multiscale residual network[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16(7): 1120–1124. doi: 10.1109/LGRS.2019.2893519.
[87]	HU Xinrui, LUO Shaojuan, HE Chunhua, et al. Infrared thermal image denoising with symmetric multi-scale sampling network[J]. Infrared Physics & Technology, 2023, 134: 104909. doi: 10.1016/j.infrared.2023.104909.
[88]	YANG Pengfei, WU Heng, CHENG Lianglun, et al. Infrared image denoising via adversarial learning with multi-level feature attention network[J]. Infrared Physics & Technology, 2023, 128: 104527. doi: 10.1016/j.infrared.2022.104527.
[89]	GUAN Juntao, LAI Rui, XIONG Ai, et al. Fixed pattern noise reduction for infrared images based on cascade residual attention CNN[J]. Neurocomputing, 2020, 377: 301–313. doi: 10.1016/j.neucom.2019.10.054.
[90]	LIU Kang, CHEN Honglei, BAO Wenzhong, et al. Thermal imaging spatial noise removal via deep image prior and step-variable total variation regularization[J]. Infrared Physics & Technology, 2023, 134: 104888. doi: 10.1016/j.infrared.2023.104888.
[91]	ULYANOV D, VEDALDI A, and LEMPITSKY V. Deep image prior[J]. International Journal of Computer Vision, 2020, 128(7): 1867–1888. doi: 10.1007/s11263-020-01303-4.
[92]	SIMKÓ A, LÖFSTEDT T, GARPEBRING A, et al. MRI bias field correction with an implicitly trained CNN[C/OL]. International Conference on Medical Imaging with Deep Learning, Zurich, Switzerland, 2022: 1125–1138.
[93]	LI Zhuo, LUO Shaojuan, CHEN Meiyun, et al. Infrared thermal imaging denoising method based on second-order channel attention mechanism[J]. Infrared Physics & Technology, 2021, 116: 103789. doi: 10.1016/j.infrared.2021.103789.
[94]	KUANG Xiaodong, SUI Xiubao, CHEN Qian, et al. Single infrared image stripe noise removal using deep convolutional networks[J]. IEEE Photonics Journal, 2017, 9(4): 3900913. doi: 10.1109/JPHOT.2017.2717948.
[95]	LI Jia, ZENG Dan, ZHANG Junjie, et al. Column-spatial correction network for remote sensing image destriping[J]. Remote Sensing, 2022, 14(14): 3376. doi: 10.3390/rs14143376.
[96]	ZHANG Hongyan, CHEN Hongyu, YANG Guangyi, et al. LR-Net: Low-rank spatial-spectral network for hyperspectral image denoising[J]. IEEE Transactions on Image Processing, 2021, 30: 8743–8758. doi: 10.1109/TIP.2021.3120037.
[97]	CHANG Yi, CHEN Meiya, YAN Luxin, et al. Toward universal stripe removal via wavelet-based deep convolutional neural network[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(4): 2880–2897. doi: 10.1109/TGRS.2019.2957153.
[98]	HE Wei, YAO Quanming, LI Chao, et al. Non-local meets global: An iterative paradigm for hyperspectral image restoration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(4): 2089–2107. doi: 10.1109/TPAMI.2020.3027563.
[99]	PAN Erting, MA Yong, MEI Xiaoguang, et al. Progressive hyperspectral image destriping with an adaptive frequencial focus[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5517312. doi: 10.1109/TGRS.2023.3297622.
[100]	LI Jia, ZHANG Junjie, HAN Jungong, et al. Progressive recurrent neural network for multispectral remote sensing image destriping[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5407318. doi: 10.1109/TGRS.2023.3324606.
[101]	ZHENG Dihan, ZHANG Xiaowen, MA Kaisheng, et al. Learn from unpaired data for image restoration: A variational bayes approach[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(5): 5889–5903. doi: 10.1109/TPAMI.2022.3215571.
[102]	CROITORU F A, HONDRU V, IONESCU R T, et al. Diffusion models in vision: A survey[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(9): 10850–10869. doi: 10.1109/TPAMI.2023.3261988.