Cloud detection algorithm based on the Orthogonal Matching Pursuit

Wang Yi; He Mingyuan; Ge Jingjing; Xiang Jie

doi:10.3788/IRLA201948.1203003

Volume 48 Issue 12

Dec. 2019

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Article Navigation > Infrared and Laser Engineering > 2019 > 48(12): 1203003-1203003(6)

Wang Yi, He Mingyuan, Ge Jingjing, Xiang Jie. Cloud detection algorithm based on the Orthogonal Matching Pursuit[J]. Infrared and Laser Engineering, 2019, 48(12): 1203003-1203003(6). doi: 10.3788/IRLA201948.1203003

Citation:

Wang Yi, He Mingyuan, Ge Jingjing, Xiang Jie. Cloud detection algorithm based on the Orthogonal Matching Pursuit[J]. Infrared and Laser Engineering, 2019, 48(12): 1203003-1203003(6). doi: 10.3788/IRLA201948.1203003

Cloud detection algorithm based on the Orthogonal Matching Pursuit

doi: 10.3788/IRLA201948.1203003

1.
Institute of Meteorology and Oceangraphy,National University of Defense Technology,Nanjing 211101,China;
2.
Unit No. 31110 of PLA,Nanjing 210016,China

Received Date: 2019-10-11
Rev Recd Date: 2019-11-21
Publish Date: 2019-12-25

Abstract

Quantitative identification of cloud is very important in meteorological satellite data retrieval, and the result of cloud detection affects the accuracy directly. In fact, the cloud detecting technology is actually a process of distinguishing the objects and background, and the purpose of detection is to extract cloud features. Therefore, much signals processing and system algorithms have been applied to the technology of cloud detection. The matching pursuit algorithm (MP) is a very effective algorithm for feature extraction, which is developed in recent years, and the Orthogonal Matching Pursuit algorithm (OMP) can improve the signal-to-noise ratio more effectively. In this paper, Orthogonal Matching Pursuit algorithm and multi-channel threshold method were combined to carry out relevant research on cloud detection of MODIS data. Based on the MODIS cloud detection results, it could be proved that the integrative algorithm of multi-channel threshold combined with the Orthogonal Matching Pursuit algorithm would be more effective to cloud detection.
- MODIS,
- multi-spectral,
- feature extraction,
- cloud detection,
- Orthogonal Matching Pursuit

References

[1]	Goodman A H, Henderson-Sellers A. Cloud detection and analysis:A review of recent progress[J]. Atmospheric Research, 1988, 21:203-228.
[2]	Wang Yi. Development and Application of the New International Earth Observation System[M]. Beijing:China Metedogical Press, 2006:4. (in Chinese)王毅. 国际新一代对地观测系统的发展及其主要应用[M].北京:气象出版社, 2006:4.
[3]	William B Rossow, Leonid C Garder. Cloud detection using satellite measurements of infrared and visible radiances for ISCCP[J]. Journal of Climate, 1993, 6:2341-2369.
[4]	Chan J. Comment on changes in tropical cyclone number, duration, and intensity in a warming environment[J]. Science, 2006, 311:1713.
[5]	Ma Fang, Zhang Qiang, Guo Ni, et al. The study of cloud detection with multi-channal data of satellite[J].Chinese Jounal of Atmosphere Science, 2007, 31(1):119-128. (in Chinese)马芳, 张强, 郭铌, 等.多通道卫星云图云检测方法的研究[J]. 大气科学, 2007, 31(1):119-128.
[6]	Li Yanbing, Li Yuanxiang, Zhai Jingqiu. A method of extracting and representing morphological feathers of satellite cloud image[J]. Jounal of Nanjing Institue Meteology, 2006, 29(5):682-687. (in Chinese)李艳兵, 李元祥, 翟景秋. 卫星云图形态特征提取和表示的一种方法[J]. 南京气象学院学报, 2006, 29(5):682-687.
[7]	Wu Yongming, Zhang Ren, Jiang Guorong, et al. A fuzzy clustering method for multi-spectral satellite image[J]. Jounal of Tropical Meteology, 2004, 20(6):689-696. (in Chinese)吴咏明, 张韧, 蒋国荣, 等. 多光谱卫星图像的一种模糊聚类方法[J]. 热带气象学报, 2004, 20(6):689-696.
[8]	Shi Chunxiang, Qu Jianhua. Cloud classification for NOAA-AVHRR data by using a neural network[J]. Acta Meteorologica Sinica, 2002, 2:123-128. (in Chinese)师春香, 瞿建华. 用神经网络方法对NOAA-AVHRR资料进行云客观分类[J]. 气象学报, 2002, 2:123-128.
[9]	Hong Mei, Zhang Ren, Sun Zhaobo. A high-dimension feature spaces clustering and corresponding weather classification for multi-spectral satellite images[J]. Journal of Remote Sensing, 2006, 2(10):42-48. (in Chinese)洪梅, 张韧, 孙照渤. 多光谱卫星云图的高维特征聚类与降水天气判别[J]. 遥感学报, 2006, 2(10):42-48.
[10]	Chen Gangyi, Ding Xuyi, Zhao Liyan. An automatical pattern recognition techniques of cloud based on fuzzy neural network[J]. Chinese Journal of Atmosphere Science, 2005, 29(5):169-176. (in Chinese)陈刚毅, 丁旭羲, 赵丽妍. 用模糊神经网络自动识别云的技术研究[J]. 大气科学, 2005, 29(5):169-176.
[11]	Guo Hongtao, Wang Yi, Liu Xiangpei, et al. Integrated optimal method of cloud detection with meteorological satellite data[J]. Journal of PLA University of Science and Technology(Nature Science Edition),2010,11(2):221-227. (in Chinese)郭洪涛, 王毅, 刘向培, 等.卫星云图云检测的一种综合优化方法[J]. 解放军理工大学学报(自然科学版), 2010, 11(2):221-227.
[12]	费文龙. 变分方法在GMS-5气象卫星云图处理中的应用研究[D]. 南京:南京理工大学, 2004.
[13]	Shuai Chunxiang, Wu Rongzhang, Xiang Xukang. Automatic segmentation of satellite image using hierarchical threshold and neural network[J]. Journal of Applied Meteorological Science, 2001, 12(1):69-78. (in Chinese)师春香, 吴蓉璋, 项续康. 多阈值和神经网络卫星云图云系自动分割实验[J]. 应用气象学报, 2001, 12(1):69-78.
[14]	Xue Juntao, Liu Zhengguang, Liu Huanzhu. Application of wavelet transforms on the boundary processing of the infrared satellite cloud image[J]. Journal of Tianjin University (Science and Technology), 2002, 35(6):736-739. (in Chinese)薛俊滔, 刘正光, 刘还珠. 小波变换在云图边缘处理中的应用[J]. 天津大学学报, 2002, 35(6):736-739.
[15]	Harsanyi J C, Chang C I. Hyperspectral image classification and dimensionality reduction:an orthogonal subspace projection approach[J]. IEEE Trans Geosci Remote Sens, 1994, 32(4):779-785.
[16]	Mallat S, Zhang Z F. Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993, 41(12):3397-3415.
[17]	Wen J M, Zhou Z C, Wang J, et al. A sharp condition for exact support recovery of sparse signals with orthogonal matching pursuit[C]//2016 IEEE International Symposium on Information Theory, IEEE, 2016:2364-2368.
[18]	Needell D, Vershynin R. Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit[J]. IEEE Journal of Selected Topics in Signal Processing, 2010, 4(2):310-316.
[19]	Needell D, Tropp J A. CoSaMP:iterative signal recovery from incomplete and inaccurate samples[J]. Applied and Computational Harmonic Analysis, 2009, 26(3):301-321.
[20]	Manolakis D, Shaw G. Detection algorithms for hyperspectral imaging applications[J]. IEEE Signal Process Lett, 2002, 19(1):29-43.
[21]	Tropp J A, Gilbert A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 2007, 53(12):4655-4666.

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

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Cloud detection algorithm based on the Orthogonal Matching Pursuit

1. Institute of Meteorology and Oceangraphy,National University of Defense Technology,Nanjing 211101,China;

2. Unit No. 31110 of PLA,Nanjing 210016,China

Received Date: 2019-10-11

Rev Recd Date: 2019-11-21

Publish Date: 2019-12-25

Key words:

Abstract: Quantitative identification of cloud is very important in meteorological satellite data retrieval, and the result of cloud detection affects the accuracy directly. In fact, the cloud detecting technology is actually a process of distinguishing the objects and background, and the purpose of detection is to extract cloud features. Therefore, much signals processing and system algorithms have been applied to the technology of cloud detection. The matching pursuit algorithm (MP) is a very effective algorithm for feature extraction, which is developed in recent years, and the Orthogonal Matching Pursuit algorithm (OMP) can improve the signal-to-noise ratio more effectively. In this paper, Orthogonal Matching Pursuit algorithm and multi-channel threshold method were combined to carry out relevant research on cloud detection of MODIS data. Based on the MODIS cloud detection results, it could be proved that the integrative algorithm of multi-channel threshold combined with the Orthogonal Matching Pursuit algorithm would be more effective to cloud detection.

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Reference (21)

[1]	Goodman A H, Henderson-Sellers A. Cloud detection and analysis:A review of recent progress[J]. Atmospheric Research, 1988, 21:203-228.
[2]	Wang Yi. Development and Application of the New International Earth Observation System[M]. Beijing:China Metedogical Press, 2006:4. (in Chinese)王毅. 国际新一代对地观测系统的发展及其主要应用[M].北京:气象出版社, 2006:4.
[3]	William B Rossow, Leonid C Garder. Cloud detection using satellite measurements of infrared and visible radiances for ISCCP[J]. Journal of Climate, 1993, 6:2341-2369.
[4]	Chan J. Comment on changes in tropical cyclone number, duration, and intensity in a warming environment[J]. Science, 2006, 311:1713.
[5]	Ma Fang, Zhang Qiang, Guo Ni, et al. The study of cloud detection with multi-channal data of satellite[J].Chinese Jounal of Atmosphere Science, 2007, 31(1):119-128. (in Chinese)马芳, 张强, 郭铌, 等.多通道卫星云图云检测方法的研究[J]. 大气科学, 2007, 31(1):119-128.
[6]	Li Yanbing, Li Yuanxiang, Zhai Jingqiu. A method of extracting and representing morphological feathers of satellite cloud image[J]. Jounal of Nanjing Institue Meteology, 2006, 29(5):682-687. (in Chinese)李艳兵, 李元祥, 翟景秋. 卫星云图形态特征提取和表示的一种方法[J]. 南京气象学院学报, 2006, 29(5):682-687.
[7]	Wu Yongming, Zhang Ren, Jiang Guorong, et al. A fuzzy clustering method for multi-spectral satellite image[J]. Jounal of Tropical Meteology, 2004, 20(6):689-696. (in Chinese)吴咏明, 张韧, 蒋国荣, 等. 多光谱卫星图像的一种模糊聚类方法[J]. 热带气象学报, 2004, 20(6):689-696.
[8]	Shi Chunxiang, Qu Jianhua. Cloud classification for NOAA-AVHRR data by using a neural network[J]. Acta Meteorologica Sinica, 2002, 2:123-128. (in Chinese)师春香, 瞿建华. 用神经网络方法对NOAA-AVHRR资料进行云客观分类[J]. 气象学报, 2002, 2:123-128.
[9]	Hong Mei, Zhang Ren, Sun Zhaobo. A high-dimension feature spaces clustering and corresponding weather classification for multi-spectral satellite images[J]. Journal of Remote Sensing, 2006, 2(10):42-48. (in Chinese)洪梅, 张韧, 孙照渤. 多光谱卫星云图的高维特征聚类与降水天气判别[J]. 遥感学报, 2006, 2(10):42-48.
[10]	Chen Gangyi, Ding Xuyi, Zhao Liyan. An automatical pattern recognition techniques of cloud based on fuzzy neural network[J]. Chinese Journal of Atmosphere Science, 2005, 29(5):169-176. (in Chinese)陈刚毅, 丁旭羲, 赵丽妍. 用模糊神经网络自动识别云的技术研究[J]. 大气科学, 2005, 29(5):169-176.
[11]	Guo Hongtao, Wang Yi, Liu Xiangpei, et al. Integrated optimal method of cloud detection with meteorological satellite data[J]. Journal of PLA University of Science and Technology(Nature Science Edition),2010,11(2):221-227. (in Chinese)郭洪涛, 王毅, 刘向培, 等.卫星云图云检测的一种综合优化方法[J]. 解放军理工大学学报(自然科学版), 2010, 11(2):221-227.
[12]	费文龙. 变分方法在GMS-5气象卫星云图处理中的应用研究[D]. 南京:南京理工大学, 2004.
[13]	Shuai Chunxiang, Wu Rongzhang, Xiang Xukang. Automatic segmentation of satellite image using hierarchical threshold and neural network[J]. Journal of Applied Meteorological Science, 2001, 12(1):69-78. (in Chinese)师春香, 吴蓉璋, 项续康. 多阈值和神经网络卫星云图云系自动分割实验[J]. 应用气象学报, 2001, 12(1):69-78.
[14]	Xue Juntao, Liu Zhengguang, Liu Huanzhu. Application of wavelet transforms on the boundary processing of the infrared satellite cloud image[J]. Journal of Tianjin University (Science and Technology), 2002, 35(6):736-739. (in Chinese)薛俊滔, 刘正光, 刘还珠. 小波变换在云图边缘处理中的应用[J]. 天津大学学报, 2002, 35(6):736-739.
[15]	Harsanyi J C, Chang C I. Hyperspectral image classification and dimensionality reduction:an orthogonal subspace projection approach[J]. IEEE Trans Geosci Remote Sens, 1994, 32(4):779-785.
[16]	Mallat S, Zhang Z F. Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993, 41(12):3397-3415.
[17]	Wen J M, Zhou Z C, Wang J, et al. A sharp condition for exact support recovery of sparse signals with orthogonal matching pursuit[C]//2016 IEEE International Symposium on Information Theory, IEEE, 2016:2364-2368.
[18]	Needell D, Vershynin R. Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit[J]. IEEE Journal of Selected Topics in Signal Processing, 2010, 4(2):310-316.
[19]	Needell D, Tropp J A. CoSaMP:iterative signal recovery from incomplete and inaccurate samples[J]. Applied and Computational Harmonic Analysis, 2009, 26(3):301-321.
[20]	Manolakis D, Shaw G. Detection algorithms for hyperspectral imaging applications[J]. IEEE Signal Process Lett, 2002, 19(1):29-43.
[21]	Tropp J A, Gilbert A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 2007, 53(12):4655-4666.

Cloud detection algorithm based on the Orthogonal Matching Pursuit

doi: 10.3788/IRLA201948.1203003

Abstract

References

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