Data preprocessing methods of domestic core spectral scanner CMS350A

doi:10.6046/gtzyyg.2017.04.12

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Abstract Hyperspectrum logging of core is one of the effective techniques for excavating geological data deeply and making a breakthrough in geological prospecting. Using hyperspectral remote sensing technology and deep rock sampling based on drilling technology has the advantages of mineral recognition. The first core scanner CMS350A in China has been developed successfully through the special project of national great scientific instruments and equipment, namely “development and marketing of core spectral scanner”. In consideration of the data collecting mechanism and characteristics of acquired core images and spectra by the scanner, the authors focused on developing the data preprocessing methods for the core image and spectrum data. A radiation correction method based on standard plate was developed for core scanning image, an interference spectrum detection and modification technology was proposed, and a model for automatic core image extraction and mosaicking was created to accurately process the data in time. These methods constitute the basis for core spectrum analysis, physic-chemical parameters inversion, and mineral analysis in future.

Keywords fractal dimension-change point method(FDCPM) remote sensing alteration anomaly self-similarity mutability ASTER

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Issue Date: 04 December 2017

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	HAN Haihui
	WANG Yilin
	YANG Min
	REN Guangli
	YANG Junlu
	LI Jianqiang
	GAO Ting

Cite this article:

HAN Haihui,WANG Yilin,YANG Min, et al. Data preprocessing methods of domestic core spectral scanner CMS350A[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(4): 73-81.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2017.04.12 OR https://www.gtzyyg.com/EN/Y2017/V29/I4/73

[1]　陈述彭,郭华东.“数字地球”与对地观测[J].地理学报,2000,55(1):9-14.
Chen S P,Guo H D.Digital earth and earth observation[J].Acta Geographica Sinica,2000,55(1):9-14.
[2]　中国地质调查局.中国地质勘查技术进展与发展展望[R].北京:中国地质调查局,2010.
China Geological Survey.Progression and Prospect of the Geological Prospecting Technology in China[R].Beijing:China Geological Survey,2010.
[3]　王润生,熊盛青,聂洪峰,等.遥感地质勘查技术与应用研究[J].地质学报,2011,85(11):1699-1743.
Wang R S,Xiong S Q,Nie H F,et al.Remote sensing technology and its application in geological exploration[J].Acta Geologica Sinica,2011,85(11):1699-1743.
[4]　刘树臣.发展新一代矿产勘探技术——澳大利亚玻璃地球计划的启示[J].地质与勘探,2003,39(5):53-56.
Liu S C.Towards the next generation of giant minerals exploration techniques:Some considerations about the glass earth[J].Geology and Prospecting,2003,39(5):53-56.
[5]　王晋年,李志忠,张立福,等.“光谱地壳”计划——探索新一代矿产勘查技术[J].地球信息科学学报,2012,14(3):344-351.
Wang J N,Li Z Z,Zhang L F,et al.“Spectral Crust” project:Research on new mineral exploration technology[J].Journal of Geo-Information Science,2012,14(3):344-351.
[6]　张金昌.地质岩心钻探技术及其在资源勘探中的应用[J].探矿工程(岩土钻掘工程),2009,36(8):1-6.
Zhang J C.Core drilling techniques and their applications in the exploration of mineral resources[J].Exploration Engineering(Rock and Soil Drilling and Tunneling),2009,36(8):1-6.
[7]　李永忠,杨光,李秀国.关于岩心数字化建设的思考[J].胜利油田职工大学学报,2008,22(4):53-54.
Li Y Z,Yang G,Li X G.On core digital construction[J].Journal of Shengli Oilfield Staff University,2008,22(4):53-54.
[8]　秦艳,王曙光.基于C/S和B/S混合模式岩芯库管理信息系统的设计与实现[J].江汉石油职工大学学报,2010,23(5):58-60.
Qin Y,Wang S G.Design and application of the core library information management system based on B/S and C/S mixed model[J].Journal of Jianghan Petroleum University of Staff and Workers,2010,23(5):58-60.
[9]　胥燕辉.铁矿岩心高光谱编录初探[J].地质找矿论丛,2006,22(s1):113-117.
Xu Y H.The preliminary study on hyperspectral core logging[J].Contributions to Geology and Mineral Resources Research,2006,22(s1):113-117.
[10] 张杰林,黄艳菊,王俊虎,等.铀矿勘查钻孔岩心高光谱编录及三维矿物填图技术研究[J].铀矿地质,2013,29(4):249-255.
Zhang J L,Huang Y J,Wang J H,et al.Hyperspectral drilling core logging and 3D mineral mapping technology for Uranium exploration[J].Uranium Geology,2013,29(4):249-255.
[11] 修连存,郑志忠,殷靓,等.岩心扫描仪光谱数据质量评估方法研究[J].光谱学与光谱分析,2015,35(8):2352-2356.
Xiu L C,Zheng Z Z,Yin L,et al.Research on assessment methods of spectrum data quality of core scan[J].Spectroscopy and Spectral Analysis,2015,35(8):2352-2356.
[12] 张国田.岩心成像技术原理与图像采集[J].录井工程,2013,24(2):37-40.
Zhang G T.Principle and image acquisition of core imaging technology[J].Mud Logging Engineering,2013,24(2):37-40.
[13] 山东省计量科学研究院.JJF 1232―2009反射率测定仪校准规范[S].济南:山东省计量科学研究院,2009.
Shandong Institute of Metrology.JJF 1232―2009 Calibration Specification for Reflectomters[S].Jinan:Shandong Institute of Metrology,2009.
[14] 焦竹青,徐保国.HSV变换和同态滤波的彩色图像光照补偿[J].计算机工程与应用,2010,46(30):142-144.
Jiao Z Q,Xu B G.Color image illumination compensation based on HSV transform and homomorphic filtering[J].Computer Engineering and Applications,2010,46(30):142-144.
[15] 吴成茂.直方图均衡化的数学模型研究[J].电子学报,2013,41(3):598-602.
Wu C M.Studies on mathematical model of histogram equalization[J].Acta Electronica Sinica,2013,41(3):598-602.
[16] 章毓晋.图像工程[M].3版.北京:清华大学出版社,2013:95-96.
Zhang Y J.Image Engineering[M].3rd ed.Beijing:Tsinghua University Press,2013:95-96.
[17] 陈春宁,王延杰.在频域中利用同态滤波增强图像对比度[J].微计算机信息,2007,23(6):264-266.
Chen C N,Wang Y J.Image contrast enhancement by homomorphic filtering in frequency field[J].Control and Management,2007,23(6):264-266.
[18] 刘毅,贾旭芬,田子建.一种基于同态滤波原理的井下光照不均图像处理方法[J].工矿自动化,2013,39(1):9-12.
Liu Y,Jia X F,Tian Z J.A processing method for underground image of uneven illumination based on homomorphic filtering theory[J].Industry and Mine Automation,2013,39(1):9-12.
[19] 王青华,王润生,郭小方.高光谱遥感技术在岩石识别中的应用[J].国土资源遥感,2000,12(4):39-43.doi:10.6046/gtzyyg.2000.04.08.
Wang Q H,Wang R S,Guo X F.Application for discrimination of rock using hyperspectral remote sensing technique[J].Remote Sensing for Land and Resources,2000,12(4):39-43.doi:10.6046/gtzyyg.2000.04.08.
[20] 王娟,师军,吴宪祥.图像拼接技术综述[J].计算机应用研究,2008,25(7):1940-1943,1947.
Wang J,Shi J,Wu X X.Survey of image mosaics techniques[J].Application Research of Computers,2008,25(7):1940-1943,1947.
[21] Lowe D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.
[22] 翟丽杰.基于特征点的改进SIFT岩心图像匹配算法[J].计算机与数字工程,2013,41(6):981-983.
Zhai L J.Improved SIFT algorithm of image match based on feature point[J].Computer and Digital Engineering,2013,41(6):981-983.

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