Citation: | TAN Cui-mei, XU Ting-fa, MA Xu, ZHANG Yu-han, WANG Xi, YAN Ge. Graph-spectral hyperspectral video restoration based on compressive sensing[J]. Chinese Optics, 2018, 11(6): 949-957. doi: 10.3788/CO.20181106.0949 |
[1] |
马晨光, 曹汛, 戴琼海, 等.高分辨率光谱视频采集研究[J].电子学报, 2015, 43(4):783-790. doi: 10.3969/j.issn.0372-2112.2015.04.022
MA CH G, CAO X, DAI Q H, et al.. Research on high resolution hyperspectral capture technique[J]. Chinese Journal of Electronics, 2015, 43(4):783-790.(in Chinese) doi: 10.3969/j.issn.0372-2112.2015.04.022
|
[2] |
付立婷, 邓河, 刘春红.新型高光谱图像快速实时目标检测与分类方法[J].光学学报, 2017, 37(2):314-322. http://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201702038.htm
FU L T, DENG H, LIU CH H. Novel fast real-time target detection and classification algorithms for hyperspectral imagery[J]. Acta Optica Sinica, 2017, 37(2):314-322.(in Chinese) http://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201702038.htm
|
[3] |
梅风华, 李超, 张玉鑫.光谱成像技术在海域目标探测中的应用[J].中国光学, 2017, 10(6):708-718. http://www.chineseoptics.net.cn/CN/abstract/abstract9565.shtml
MEI F H, LI CH, ZH Y X. Application of spectral imaging technology in maritime target detection[J]. Chinese Optics, 2017, 10(6):708-718.(in Chinese) http://www.chineseoptics.net.cn/CN/abstract/abstract9565.shtml
|
[4] |
CLAUDIA V C, DIANA F G, HENRY A F. Sparse representations of dynamic scenes for compressive spectral video sensing[J]. Dyna Revista De La Facultad De Minas, 2016, 83(195):42-51.
|
[5] |
WAGADARIKAR A, PITSIANIS N, SUN X, et al.. Video rate spectral imaging using a coded aperture snapshot spectral imager[J]. Optics Express, 2009, 17(8):6368-6388. doi: 10.1364/OE.17.006368
|
[6] |
CAO X, DU H, DAI Q H, et al.. A prism-mask system for multispectral video acquisition[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2011, 33(12):2423-2435. http://dl.acm.org/citation.cfm?id=2068459.2068565
|
[7] |
AJMAL M, RICHARD H. Hyperspectral video restoration using optical flow and sparse coding[J]. Optics Express, 2012, 20(10):10658-10673. doi: 10.1364/OE.20.010658
|
[8] |
BARNICH O, VANDROOGENBROECK M. ViBe:a universal background subtraction algorithm for video sequences[J]. IEEE Transactions on Image Processing, 2011, 20(6):1709-1724. doi: 10.1109/TIP.2010.2101613
|
[9] |
丁洁, 况立群, 韩燮.基于ViBe的运动目标检测改进方法[J].计算机工程与设计, 2017, 38(2):374-378. http://d.old.wanfangdata.com.cn/Periodical/jsjgcysj201702018
DING J, KUANG L Q, HAN X. Improved moving object detection method based on ViBe[J]. Computer Engineering and Design, 2017, 38(2):374-378.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/jsjgcysj201702018
|
[10] |
胡昭华, 张维新, 王珏, 等.基于改进ViBe的运动目标检测算法[J].电子技术应用, 2017, 43(4):129-132. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dzjsyy201704034
HU ZH H, ZHANG W X, WANG J, et al.. Moving object detection algorithm based on improved ViBe[J]. Application of Electronic Technique, 2017, 43(4):129-132.(in Chinese) http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dzjsyy201704034
|
[11] |
戴琼海, 付长军, 季向阳.压缩感知研究[J].计算机学报, 2011, 34(3):3425-3434. http://d.old.wanfangdata.com.cn/Periodical/dianzixb200905028
DAI Q H, FU CH J, JI X Y. Research on compressed sensing[J]. Chinese Journal of Computers, 2011, 34(3):3425-3434.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/dianzixb200905028
|
[12] |
朱明, 高文, 郭立强.压缩感知理论在图像处理领域的应用[J].中国光学, 2011, 4(5):441-447. doi: 10.3969/j.issn.2095-1531.2011.05.006
ZHU M, GAO W, GUO L Q. Application of compressed sensing theory in image processing[J]. Chinese Optics, 2011, 4(5):441-447.(in Chinese) doi: 10.3969/j.issn.2095-1531.2011.05.006
|
[13] |
王忠良, 冯燕, 肖华, 等.高光谱图像的分布式压缩感知成像与重构[J].光学精密工程, 2015, 23(4):1131-1137. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201504028
WANG ZH L, FENG Y, XIAO H, et al.. Distributed compressive sensing imaging and reconstruction of hyperspectral imagery[J]. Opt. Precision Eng., 2015, 23(4):1131-1137.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201504028
|
[14] |
杨鹰, 孔玲君, 刘真.基于压缩感知的多光谱图像去马赛克算法[J].液晶与显示, 2017, 32(1):56-61. http://d.old.wanfangdata.com.cn/Periodical/yjyxs201701010
YANG Y, KONG L J, LIU ZH. Multi-spectral demosaicking method based on compressive sensing[J]. Chinese Journal of Liquid Crystals and Displays, 2017, 32(1):56-61.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/yjyxs201701010
|
[15] |
汪琪, 马灵玲, 唐伶俐, 等.基于光谱稀疏模型的高光谱压缩感知重构[J].红外与毫米波学报, 2016, 35(6):723-730. http://d.old.wanfangdata.com.cn/Periodical/hwyhmb201606015
WANG Q, MA L L, TANG L L, et al.. Hyperspectral compressive sensing reconstruction based on spectral sparse model[J]. Journal of Infrared and Millimeter Waves, 2016, 35(6):723-730.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/hwyhmb201606015
|
[16] |
王晗, 王阿川, 苍圣.基于压缩感知的高光谱遥感影像重构方法研究[J].液晶与显示, 2017, 32(3):219-226. http://d.old.wanfangdata.com.cn/Periodical/yjyxs201703009
WANG H, WANG A CH, C SH. Hyperspectral remote sensing image reconstruction method based on compressive sensing[J]. Chinese Journal of Liquid Crystals and Displays, 2017, 32(3):219-226.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/yjyxs201703009
|
[17] |
GAN L. Block compressed sensing of natural images[C]. Proceedings of the 15th International Conference on Digital Signal Processing, Cardiff, Wales, 2007: 403-406.
|
[18] |
DONG W SH, ZHANG L, SHI G M, et al.. Image deblurring and super-resolution by adaptive sparse domain selection and adaptive regularization[J]. IEEE Transactions on Image Processing, 2011, 20(7):1838-1857. doi: 10.1109/TIP.2011.2108306
|
[19] |
首照宇, 吴广祥, 张彤.基于PCA子字典学习的图像超分辨率重建[J].计算机工程与设计, 2015, 36(11):3025-3029. http://d.old.wanfangdata.com.cn/Periodical/jsjgcysj201511029
SHOU ZH Y, WU G X, ZHANG T. Image super-resolution reconstruction via PCA sub-dictionaries learning[J]. Computer Engineering and Design, 2015, 36(11):3025-3029.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/jsjgcysj201511029
|
[20] |
WRIGHT S J, NOWAK R D, FIGUEIREDO M A T. Sparse reconstruction by separable approximation[J]. IEEE Transactions on Signal Processing, 2009, 57(7):2479-2493. doi: 10.1109/TSP.2009.2016892
|
[1] | 涡旋光束轨道角动量的十字线检测法[J]. Chinese Optics. doi: 10.37188/CO.2024-0209 |
[2] | WANG Chi, SHEN Chen, HUANG Qing, ZHANG Guo-feng, LU Han, CHEN Jin-bo. Self-supervised learning enhancement and detection methods for nocturnal animal images[J]. Chinese Optics, 2024, 17(5): 1087-1097. doi: 10.37188/CO.2024-0011 |
[3] | WANG Bo-xiao, SONG Yan-song, DONG Xiao-na. Indistinguishable points attention-aware network for infrared small object detection[J]. Chinese Optics, 2024, 17(3): 538-547. doi: 10.37188/CO.2023-0178 |
[4] | WANG Hui-qin, HOU Wen-bin, HUANG Rui, CHEN Dan. Spatial pulse position modulation multi-classification detector based on deep learning[J]. Chinese Optics, 2023, 16(2): 415-424. doi: 10.37188/CO.2022-0106 |
[5] | LIU Yan-lei, LI Meng-zhe, WANG Xuan-xuan. Lightweight YOLOv5s vehicle infrared image target detection[J]. Chinese Optics, 2023, 16(5): 1045-1055. doi: 10.37188/CO.2022-0254 |
[6] | JI Xiao-qiang, LIU Zhen-yao, LI Bing-lin, RAO Zhi, LI Gui-wen, SU Li-wei. Non-contact perception of physiological parameters from videos of faces[J]. Chinese Optics, 2022, 15(2): 276-285. doi: 10.37188/CO.2021-0157 |
[7] | LI Yun-hui. Review of physical implementation architecture in compressive spectral imaging system[J]. Chinese Optics, 2022, 15(5): 929-945. doi: 10.37188/CO.2022-0104 |
[8] | LI Yi-ting, WANG Ling-jie, ZHANG Yu-hui, LIU Ming-xin. Optical design of visual and infrared imaging system based on space-based platform[J]. Chinese Optics, 2021, 14(6): 1495-1503. doi: 10.37188/CO.2019-0255 |
[9] | ZHANG Rui-yan, JIANG Xiu-jie, AN Jun-she, CUI Tian-shu. Design of global-contextual detection model for optical remote sensing targets[J]. Chinese Optics, 2020, 13(6): 1302-1313. doi: 10.37188/CO.2020-0057 |
[10] | LIU Ming-xin, ZHANG Xin, WANG Ling-jie, SHI Guang-wei, WU Hong-bo, FU Qiang. Optimization of matching coded aperture with detector based on compressed sensing spectral imaging technology[J]. Chinese Optics, 2020, 13(2): 290-301. doi: 10.3788/CO.20201302.0290 |
[11] | ZHANG Sai-wen, LIN Dan-ying, YU Bin, LENG Xiao-ling, ZHANG Guang-fu, TIAN Ye, TAN Wei-shi. Three-dimensional single-molecule localization microscopy imaging based on compressed sensing[J]. Chinese Optics, 2020, 13(5): 1065-1074. doi: 10.37188/CO.2020-0003 |
[12] | HUANG Le-hong, CAO Li-hua, LI Ning, LI Yi. A state perception method for infrared dim and small targets with deep learning[J]. Chinese Optics, 2020, 13(3): 527-536. doi: 10.3788/CO.2019-0120 |
[13] | LIU Bo, XU Ting-fa, LI Xiang min, SHI Guo kai, HUANG Bo. Adaptive context-aware correlation filter tracking[J]. Chinese Optics, 2019, 12(2): 265-273. doi: 10.3788/CO.20191202.0265 |
[14] | WANG Chun-zhe, AN Jun-she, JIANG Xiu-jie, XING Xiao-xue. Region proposal optimization algorithm based on convolutional neural networks[J]. Chinese Optics, 2019, 12(6): 1348-1361. doi: 10.3788/CO.20191206.1348 |
[15] | YAN Ge, XU Ting-fa, MA Xu, ZHANG Yu-han, WANG Xi, TAN Cui-mei. Hyperspectral image compression sensing based on dynamic measurement[J]. Chinese Optics, 2018, 11(4): 550-559. doi: 10.3788/CO.20181104.0550 |
[16] | YANG Hang, WU Xiao-tian, WANG Yu-qing. Image restoration approach based on structure dictionary learning[J]. Chinese Optics, 2017, 10(2): 207-218. doi: 10.3788/CO.20171002.0207 |
[17] | LI Feng, ZHAO Yan, WANG Shi-gang, CHEN He-xin. Video scene mutation change detection combined with SIFT algorithm[J]. Chinese Optics, 2016, 9(1): 74-80. doi: 10.3788/CO.20160901.0074 |
[18] | HE Yang, HUANG Wei, WANG Xin-hua, HAO Jian-kun. Super-resolution image reconstruction based on sparse threshold[J]. Chinese Optics, 2016, 9(5): 532-539. doi: 10.3788/CO.20160905.0532 |
[19] | LIU Wei-ning. Dim target detection based on wavelet field diffusion filter[J]. Chinese Optics, 2011, 4(5): 503-508. |
[20] | ZHU Ming, GAO Wen, GUO Li-qiang. Application of compressed sensing theory in image processing[J]. Chinese Optics, 2011, 4(5): 441-447. |