Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2014, Vol. 26 Issue (4) : 8-13     DOI: 10.6046/gtzyyg.2014.04.02
Technology and Methodology |
Hyperspectral image band grouping and reordering based on fuzzy similarity and improved Prim algorithm
ZHANG Zhuan, MA Yu, CAI Wei
School of Electronics and Information, Northwestern Polytechnic University, Xi'an 710072, China
Download: PDF(857 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

Traditional hyperspectral image band grouping and reordering algorithms based on Prim require calculating the correlation coefficients between all bands, and full rank correlation coefficient matrix is used as the adjacent matrix for comparison, which causes high computational complexity. Combining the similarity measurement of fuzzy mathematics theory with the characteristics of the hyperspectral image, the maximum and minimum closeness(MMC)which possesses the characteristics of less computation is used as a parameter for measuring the correlation of the hyperspectral image bands. Then the adjacent matrix of MMC is processed into a sparse matrix and the effective bands is extracted for reordering. In this way, the number of bands used for ordering and the required times for band comparison will be significantly reduced. Experimental results show that, compared with the traditional Prim algorithm, the proposed algorithm greatly reduces the calculation complexity of the hyperspectral image band ordering while maintaining compression efficiency, and the average running time for band ordering has been reduced by 27%.

Keywords Lushan earthquake      secondary geological disaster      remote sensing survey      spatial distribution     
:  TP751.1  
Issue Date: 17 September 2014
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
GUO Zhaocheng
TONG Liqiang
ZHENG Xiongwei
QI Jianwei
WANG Jianchao
Cite this article:   
GUO Zhaocheng,TONG Liqiang,ZHENG Xiongwei, et al. Hyperspectral image band grouping and reordering based on fuzzy similarity and improved Prim algorithm[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 8-13.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2014.04.02     OR     https://www.gtzyyg.com/EN/Y2014/V26/I4/8

[1] 万建伟,粘永健,苏令华,等.实用高光谱遥感图像压缩[M].北京:国防工业出版社,2012. Wan J W,Nian Y J,Su L H,et al.Applied Compression of Hyperspectral Remote Sensing Images[M].Beijing:National and Defense Industry Press,2012.

[2] 罗建书,周敏,孙蕾.高光谱遥感图像数据压缩[M].北京:国防工业出版社,2011. Luo J S,Zhou M,Sun L.Data Compression of Hyperspectral Remote Sensing Image[M].Beijing:National and Defense Industry Press,2011.

[3] Toivanen P,Kubasova O, Mielikainen J.Correlation-based band- ordering heuristic for lossless compression of hyperspectral sounder data[J].IEEE Geoscience and Remote Sensing Letters,2005,2(1):50-54.

[4] Tate S R.Band ordering in lossless compression of multispectral images[J].IEEE Transactions on Computers,1997,46(4):477-483.

[5] Fernhdez G.Ubiergo lossless region-based multispectral image compression[J].IPA97,1997,443:15-17.

[6] Toivanen P,Kubasova O, Mielikainen J.Correlation-based band- ordering heuristic for lossless compression of hyperspectral sounder data[J].IEEE Geoscience and Remote Sensing Letters,2005,2(1):50-54.

[7] Pizzolante R,Carpentieri B.Visualization,band ordering and compression of hyperspectral images[J].Algorithms,2012,5(1):76-97.

[8] 刘法贵,赵娟.模糊贴近度及应用[J].华北水利水电学院学报,2006,27(3):104-106. Liu F G,Zhao J.Fuzzy similarity and application[J].Journal of North China Institute of Water Conservancy and Hydropower,2006,27(3):104-106.

[9] 钟新联.统计学原理[M].上海:立信会计出版社,2008. Zhon X L.Principles of Statistics[M].Shanghai:Lixin Accounting Press,2008.

[10] 江波,张黎.基于Prim算法的最小生成树优化研究[J].计算机工程与设计,2009,30(13):3244-3247. Jiang B,Zhang L.Research on minimum spanning tree based on prim algorithm[J].Computer Engineering and Design,2009,30(13):3244-3247.

[11] 孟广武.区间值Fuzzy集的基本理论[J].应用数学,1993,6(2):212-217. Meng G W.Basic theory for interval-valued Fuzzy sets[J].Mathe- matica Applicata,1993,6(2):212-217.

[12] 袁宏俊,杨桂元.基于最大-最小贴近度的最优组合预测模型[J].运筹与管理,2010,19(2):116-128. Yuan H J,Yang G Y.The combination forecast model based on the biggest-smallest approach degree[J].Operations Research and Management,2010,19(2):116-128.

[13] 丁国强,吕治国.基于Prim算法最小生成树优化的研究[J].甘肃联合大学学报:自然科学版,2009,23(5):67-69. Ding G Q,Lü Z G.Optimization algorithm of minimum spanning tree based on Prim[J].Gansu Union University:Natural Science,2009,23(5):67-69.

[14] Zhang J,Liu G Z.An efficient reordering prediction-based lossless compression algorithm for hyperspectral images[J].IEEE Geoscience and Remote Sensing Letters,2007,4(2):283-287.

[15] 刘银年,薛永祺,王建宇,等.实用型模块化成像光谱仪[J].红外与毫米波学报,2002,21(1):9-14. Liu Y N,Xue Y Q,Wang J Y.Operational modular imaging spectrometer[J].Journal of Infrared and Millimeter Waves,2002,21(1):9-14.

[1] WANG Shuang, ZHANG Lei, ZHANG Junyong, WANG Yile. Characteristics of GIS applications in national fitness[J]. Remote Sensing for Natural Resources, 2021, 33(4): 265-271.
[2] HAO Guzhuang, GAN Fuping, YAN Baikun, LI Xianqing, HU Huidong. Remote sensing survey and driving force analysis of area change of Hongyashan Reservoir in the past twenty years[J]. Remote Sensing for Land & Resources, 2021, 33(2): 192-201.
[3] Ke ZHANG, Jianzhong LIU, Weiming CHENG. Morphological features and spatial distribution of the lunar Copernican secondary craters[J]. Remote Sensing for Land & Resources, 2019, 31(1): 255-263.
[4] Yuling ZHAO. Remote sensing survey and proposal for protection of the natural resources in Guangdong-Hong Kong-Macao Greater Bay Area[J]. Remote Sensing for Land & Resources, 2018, 30(4): 139-147.
[5] Yuanwen ZENG, Yi DI, Yan HU, Jing CHEN, Songjiang DUAN. An analysis of spatial distribution and optimization of rural settlements:A case study of Niejia Village in Shitan Town,Hechuan District,Chongqing[J]. Remote Sensing for Land & Resources, 2018, 30(3): 113-119.
[6] Min YANG, Guijun YANG, Yanjie WANG, Yongfeng ZHANG, Zhihong ZHANG, Chenhong SUN. Remote sensing analysis of temporal-spatial variations of urban heat island effect over Beijing[J]. Remote Sensing for Land & Resources, 2018, 30(3): 213-223.
[7] Rui LIU, Xu JIANG, Jing ZHAO, Yunfan LI. GIS based research on the spatial distribution of population density in illegal buildings in Shenzhen City[J]. Remote Sensing for Land & Resources, 2018, 30(1): 233-237.
[8] ZHAO Yuling. Remote sensing survey and proposal for protection of the shoreline and the mangrove wetland in Guangdong Province[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(s1): 114-120.
[9] YAO Zhenhai, QIU Xinfa, SHI Guoping, ZHANG Xiliang. An analysis of spatial distribution characteristics of monthly mean NDVI in the past ten years in China[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(2): 181-186.
[10] SHI Yunxia, WANG Fanxia, WU Zhaopeng. Multi-simulation of spatial distribution of land use based on CLUE-S in Jinhe Watershed[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 154-160.
[11] YANG Bin, ZHAN Jinfeng, LI Maojiao. Evaluation of environmental vulnerability in the upper reaches of the Minjiang River[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 138-144.
[12] WEI Yongming, WEI Xianhu, CHEN Yu. Analysis of distribution regularity and development tendency of earthquake secondary geohazards in Yingxiu-Maoxian section along the Minjiang River[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 179-186.
[13] GUO Zhaocheng, TONG Liqiang, ZHENG Xiongwei, QI Jianwei, WANG Jianchao. Remote sensing survey of secondary geological disasters triggered by Lushan earthquake in Sichuan Province and tentative discussion on disaster characteristics[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(3): 99-105.
[14] TONG Liqiang, NIE Hongfeng, LI Jiancun, GUO Zhaocheng. Survey of large-scale debris flow and study of its development characteristics using remote sensing technology in the Himalayas[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(4): 104-112.
[15] LUAN Zhuoran, ZHOU Zhiyong, LU Li, ZHANG Zhike, LI Bin, YU Qian. Remote sensing survey of brick clay exploitation situation and eco-environment of central Hebei (Jizhong) plain[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(4): 143-146.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech