19.6.3.13 Mineral Composition Analysis

Chapter Contents (Back)
Application, Minerals. Minerals. See also Geological Analysis, Rocks.

Pong, T.C., Haralick, R.M., Craig, J.R., Yoon, R.H., Choi, W.Z.,
The Application of Image Analysis Techniques to Mineral Processing,
PRL(2), 1983, pp. 117-123. BibRef 8300

Larsen, R.[Rasmus], Nielsen, A.A.[Allan Aasbjerg], Flesche, H.[Harald],
Sensitivity study of a semi-automatic training set generator,
PRL(21), No. 13-14, December 2000, pp. 1175-1182. 0011
BibRef
Earlier:
Sensitivity Study of a Semi-automatic Supervised Classifier Applied to Minerals from X-Ray Mapping Images,
SCIA99(Statistical Methods). BibRef

Nielsen, A.A.[Allan A.], Larsen, R.[Rasmus],
Canonical Analysis of Sentinel-1 Radar and Sentinel-2 Optical Data,
SCIA17(II: 147-158).
Springer DOI 1706
BibRef

Larsen, R.[Rasmus], Hilger, K.B.[Klaus Baggesen],
Probabilistic Generative Modelling,
SCIA03(861-868).
Springer DOI 0310
BibRef

Hilger, K.B., Nielsen, A.A., Larsen, R.,
A Scheme for Initial Exploratory Data Analysis of Multivariate Image Data,
SCIA01(O-Tu4A). 0206
BibRef

Ross, B.J., Fueten, F., Yashkir, D.Y.,
Automatic mineral identification using genetic programming,
MVA(13), No. 2 2001, pp. 61-69.
Springer DOI 0201
BibRef

Galvao, L.S.[Lenio Soares], Formaggio, A.R.[Antonio Roberto], Couto, E.G.[Eduardo Guimaraes], Roberts, D.A.[Dar A.],
Relationships between the mineralogical and chemical composition of tropical soils and topography from hyperspectral remote sensing data,
PandRS(63), No. 2, March 2008, pp. 259-271.
WWW Link. 0803
Hyperspectral remote sensing; Tropical soils; AVIRIS; Topography; Mineral identification BibRef

Zaini, N., van der Meer, F., van der Werff, H.,
Effect of Grain Size and Mineral Mixing on Carbonate Absorption Features in the SWIR and TIR Wavelength Regions,
RS(4), No. 4, April 2012, pp. 987-1003.
DOI Link 1202
BibRef

van der Werff, H.[Harald], van der Meer, F.[Freek],
Sentinel-2 for Mapping Iron Absorption Feature Parameters,
RS(7), No. 10, 2015, pp. 12635.
DOI Link 1511
BibRef

Murphy, R.J.[Richard J.], Monteiro, S.T.[Sildomar T.],
Mapping the distribution of ferric iron minerals on a vertical mine face using derivative analysis of hyperspectral imagery (430-970 nm),
PandRS(75), No. 1, January 2013, pp. 29-39.
Elsevier DOI 1301
Mining; Iron ore; Remote sensing; Hyperspectral; Derivative analysis; Banded iron formation BibRef

de Q. da Silva, A.[Arnaldo], Paradella, W.R.[Waldir R.], Freitas, C.C.[Corina C.], Oliveira, C.G.[Cleber G.],
Evaluation of Digital Classification of Polarimetric SAR Data for Iron-Mineralized Laterites Mapping in the Amazon Region,
RS(5), No. 6, 2013, pp. 3101-3122.
DOI Link 1307
BibRef

Liu, L.[Lei], Zhou, J.[Jun], Jiang, D.[Dong], Zhuang, D.[Dafang], Mansaray, L.R.[Lamin R.], Zhang, B.[Bing],
Targeting Mineral Resources with Remote Sensing and Field Data in the Xiemisitai Area, West Junggar, Xinjiang, China,
RS(5), No. 7, 2013, pp. 3156-3171.
DOI Link 1307
BibRef

Murphy, R.J., Schneider, S., Monteiro, S.T.,
Consistency of Measurements of Wavelength Position From Hyperspectral Imagery: Use of the Ferric Iron Crystal Field Absorption at sim900 nm as an Indicator of Mineralogy,
GeoRS(52), No. 5, May 2014, pp. 2843-2857.
IEEE DOI 1403
Geology BibRef

Chen, J., Richard, C., Honeine, P.,
Nonlinear Estimation of Material Abundances in Hyperspectral Images With L_1-Norm Spatial Regularization,
GeoRS(52), No. 5, May 2014, pp. 2654-2665.
IEEE DOI 1403
L_1 -norm regularization BibRef

Notesco, G.[Gila], Kopacková, V.[Veronika], Rojík, P.[Petr], Schwartz, G.[Guy], Livne, I.[Ido], Dor, E.B.[Eyal Ben],
Mineral Classification of Land Surface Using Multispectral LWIR and Hyperspectral SWIR Remote-Sensing Data. A Case Study over the Sokolov Lignite Open-Pit Mines, the Czech Republic,
RS(6), No. 8, 2014, pp. 7005-7025.
DOI Link 1410
BibRef

Mielke, C.[Christian], Boesche, N.K.[Nina Kristine], Rogass, C.[Christian], Kaufmann, H.[Hermann], Gauert, C.[Christoph], de Wit, M.[Maarten],
Spaceborne Mine Waste Mineralogy Monitoring in South Africa, Applications for Modern Push-Broom Missions: Hyperion/OLI and EnMAP/Sentinel-2,
RS(6), No. 8, 2014, pp. 6790-6816.
DOI Link 1410
BibRef

Schneider, S.[Sven], Murphy, R.J.[Richard J.], Melkumyan, A.[Arman],
Evaluating the performance of a new classifier: the GP-OAD: A comparison with existing methods for classifying rock type and mineralogy from hyperspectral imagery,
PandRS(98), No. 1, 2014, pp. 145-156.
Elsevier DOI 1411
Hyperspectral BibRef

Huo, H.Y.[Hong-Yuan], Ni, Z.[Zhuoya], Jiang, X.G.[Xiao-Guang], Zhou, P.[Ping], Liu, L.[Liang],
Mineral Mapping and Ore Prospecting with HyMap Data over Eastern Tien Shan, Xinjiang Uyghur Autonomous Region,
RS(6), No. 12, 2014, pp. 11829-11851.
DOI Link 1412
BibRef

Cochrane, C.J., Blacksberg, J.,
A Fast Classification Scheme in Raman Spectroscopy for the Identification of Mineral Mixtures Using a Large Database With Correlated Predictors,
GeoRS(53), No. 8, August 2015, pp. 4259-4274.
IEEE DOI 1506
Raman spectra BibRef

Wang, D., Bischof, L., Lagerstrom, R., Hilsenstein, V., Hornabrook, A., Hornabrook, G.,
Automated Opal Grading by Imaging and Statistical Learning,
SMCS(46), No. 2, February 2016, pp. 185-201.
IEEE DOI 1601
Ash BibRef

Schreiner, S.[Simon], Buddenbaum, H.[Henning], Emmerling, C.[Christoph], Steffens, M.[Markus],
VNIR/SWIR Laboratory Imaging Spectroscopy for Wall-to-Wall Mapping of Elemental Concentrations in Soil Cores,
PFG(2015), No. 6, 2015, pp. 423-435.
DOI Link 1601
BibRef

Hecker, C., Riley, D., van der Meijde, M., van der Meer, F.D.,
Noise Simulation and Correction in Synthetic Airborne TIR Data for Mineral Quantification,
GeoRS(54), No. 3, March 2016, pp. 1545-1553.
IEEE DOI 1603
Data models BibRef

Mielke, C.[Christian], Rogass, C.[Christian], Boesche, N.[Nina], Segl, K.[Karl], Altenberger, U.[Uwe],
EnGeoMAP 2.0: Automated Hyperspectral Mineral Identification for the German EnMAP Space Mission,
RS(8), No. 2, 2016, pp. 127.
DOI Link 1603
BibRef

Price, M.A.[Mark A.], Ramsey, M.S.[Michael S.], Crown, D.A.[David A.],
Satellite-Based Thermophysical Analysis of Volcaniclastic Deposits: A Terrestrial Analog for Mantled Lava Flows on Mars,
RS(8), No. 2, 2016, pp. 152.
DOI Link 1603
With IR data. BibRef

Yokoya, N.[Naoto], Chan, J.C.W.[Jonathan Cheung-Wai], Segl, K.[Karl],
Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images,
RS(8), No. 3, 2016, pp. 172.
DOI Link 1604
BibRef

Aligholi, S.[Saeed], Lashkaripour, G.R.[Gholam Reza], Khajavi, R.[Reza], Razmara, M.[Morteza],
Automatic mineral identification using color tracking,
PR(65), No. 1, 2017, pp. 164-174.
Elsevier DOI 1702
Automated mineral identification BibRef

Adep, R.N.[Ramesh Nityanand], shetty, A.[Amba], Ramesh, H.,
EXhype: A tool for mineral classification using hyperspectral data,
PandRS(124), No. 1, 2017, pp. 106-118.
Elsevier DOI 1702
Artificial neural network BibRef

Liu, H.J.[Hua-Jian], Lee, S.H.[Sang-Heon], Chahl, J.S.[Javaan Singh],
Transformation of a high-dimensional color space for material classification,
JOSA-A(34), No. 4, April 2017, pp. 523-532.
DOI Link 1704
Image processing; Machine vision; Remote sensing and sensors BibRef


Patel, A.K., Chatterjee, S., Gorai, A.K.,
Development of online machine vision system using support vector regression (SVR) algorithm for grade prediction of iron ores,
MVA17(149-152)
DOI Link 1708
Feature extraction, Image color analysis, Iron, Machine vision, Ores, Support vector machines, Training BibRef

Georgoulis, S., Vanweddingen, V., Proesmans, M., Van Gool, L.J.,
Material Classification under Natural Illumination Using Reflectance Maps,
WACV17(244-253)
IEEE DOI 1609
Cameras, Context, Lighting, Manifolds, Metals, Shape, Three-dimensional, displays BibRef

Zhang, Y.[Yan], Ozay, M., Liu, X.[Xing], Okatani, T.,
Integrating deep features for material recognition,
ICPR16(3697-3702)
IEEE DOI 1705
Benchmark testing, Computational modeling, Employment, Entropy, Feature extraction, Glass, Object, recognition BibRef

Su, S.C.[Shuo-Chen], Heide, F.[Felix], Swanson, R.[Robin], Klein, J.[Jonathan], Callenberg, C.[Clara], Hullin, M.[Matthias], Heidrich, W.[Wolfgang],
Material Classification Using Raw Time-of-Flight Measurements,
CVPR16(3503-3511)
IEEE DOI 1612
BibRef

Oyen, D., Lanza, N., Porter, R.,
Discovering compositional trends in Mars rock targets from ChemCam spectroscopy and remote imaging,
AIPR15(1-8)
IEEE DOI 1605
Mars BibRef

Bianconi, F.[Francesco], Bello, R.[Raquel], Fernández, A.[Antonio], González, E.[Elena],
On Comparing Colour Spaces From a Performance Perspective: Application to Automated Classification of Polished Natural Stones,
CMTR15(71-78).
Springer DOI 1511
BibRef

Baklanova, O., Shvets, O.,
Cluster analysis methods for recognition of mineral rocks in the mining industry,
IPTA14(1-5)
IEEE DOI 1503
image colour analysis BibRef

Baklanova, O.E.[Olga E.], Shvets, O.Y.[Olga Ya.],
Development of Methods and Algorithms of Reduction for Image Recognition to Assess the Quality of the Mineral Species in the Mining Industry,
ICCVG14(75-83).
Springer DOI 1410
BibRef

Catakli, A.[Aycan], Mahdi, H.[Hanan], Al-Shukri, H.[Haydar],
Attribute analyses of GPR data for heavy minerals exploration,
AIPR12(1-9)
IEEE DOI 1307
BibRef
Earlier:
Texture analysis of GPR data as a tool for depicting soil mineralogy,
AIPR11(1-8).
IEEE DOI 1204
geophysical prospecting BibRef

Zhou, L.L.[Lin-Li], Hu, G.D.[Guang-Dao],
Mineralization Information Extraction Using ETM Remote Sensing Image,
CISP09(1-3).
IEEE DOI 0910
BibRef

Wang, W.X.[Wei-Xing], Li, L.[Lei],
Pattern Recognition and Computer vision for Mineral Froth,
ICPR06(IV: 622-625).
IEEE DOI 0609
BibRef

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Automated Measurement Systems, Close Range Photogrammetry .


Last update:Sep 22, 2017 at 21:00:01