References
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Melgani F, Bruzzone L (2002) Support vector machines for classification of hyperspectral
remote-sensing images. Proceedings of the IEEE International Geoscience and Remote
Sensing Symposium 1, pp 506-508
Mueller D, Hammerstorm D (1992) A neural network system component. Proceedings of
the International Joint Conference on Neural Networks, pp 1258-1264.
Naesset E (1996) Conditional Tau coefficient for assessment of producer's accuracy of
classified remotely sensed data. ISPRS Journal of Photogrammetry and Remote Sensing
51:91-98
Rast M, Hook SJ, Elvidge CD, Alley RE (1991) An evaluation of techniques for the extraction of mineral absorption features from high spectral resolution remote sensing data.
Photogrammetric Engineering and Remote Sensing 57(10): 1303-1309
Richards JA, Jia X (1999) Remote sensing digital image analysis: an introduction. SpringerVerlag, Berlin
Roberts RS (2000) Characterization of hyperspectral data using a genetic algorithm. Proceedings of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers
1, pp 169-173
Rosenfeld GH, Fitzpatrick-Lins K (1986) A coefficient of agreement as a measure of thematic
classification accuracy. Photogrammetric Engineering and Remote Sensing 52: 223-227
Saha AK, Arora MK, Csaplovics E, Gupta RP (2004) Land cover classification using IRS lC
LISS and topographic data in a rugged terrain in Himalayas. Geo Carto International
(Revision sent)
Schalkoff RJ (1997) Artificial neural networks. McGraw-Hill, New York
Settle JJ, Drake NA (1993) Linear mixing and the estimation of ground cover proportions.
International Journal of Remote Sensing 14: 1159-1177
Simone G, Farina A, Morabito FC, Serpico SB, Bruzzone L (2002) Image fusion techniques
for remote sensing applications. Information Fusion 3: 3-15
Smith GM, Milton EJ (1999) The use of the empirical line method to calibrate remotely
sensed data to reflectance. International Journal of Remote Sensing 20: 2653-2662
Stehman SV (1997) Selecting and interpreting measures of thematic classification accuracy.
Remote Sensing of the Environment 62: 77-89
Stehman SV (1999) Basic probability sampling designs for thematic map accuracy assessment. International Journal of Remote Sensing 20: 2423-2441
Story M, Congalton RG (1986) Accuracy assessment: a user's perspective. Remote Sensing
of the Environment 52(3): 397-399
Swain PH, Davis SM (eds) (1978) Remote sensing: the quantitative approach, McGraw Hill,
New York
Ullman RE (1999) HDF-EOS, NASA's standard data product distribution format for the
Earth Observing System data information system. Proceedings of the IEEE International
Geoscience and Remote Sensing Symposium 1, pp 276-278
Varshney PK, Chen H, Ramac LC, Uner M, Ferris D, Alford M (1999) Registration and fusion
of infrared and millimeter wave images for concealed weapon detection. Proceedings
of the IEEE International Conference on Image Processing 3, pp 532-536
Yu X, HoffLE, Reed IS, Chen AM, Stotts LB (1997) Automatic target detection and recognition in multiband imagery: a unified ML detection and estimation approach. IEEE
Transactions on Image Processing 6(1): 143-156
Zhang Z, Blum RS (1999) A categorization and study of multiscale-decomposition-based
image fusion schemes. Proceedings of the IEEE, pp 1315-1328
Zitova B, Flusser J (2003) Image registration methods: a survey. Image and Vision Computing, pp 977-1000
85
Melgani F, Bruzzone L (2002) Support vector machines for classification of hyperspectral
remote-sensing images. Proceedings of the IEEE International Geoscience and Remote
Sensing Symposium 1, pp 506-508
Mueller D, Hammerstorm D (1992) A neural network system component. Proceedings of
the International Joint Conference on Neural Networks, pp 1258-1264.
Naesset E (1996) Conditional Tau coefficient for assessment of producer's accuracy of
classified remotely sensed data. ISPRS Journal of Photogrammetry and Remote Sensing
51:91-98
Rast M, Hook SJ, Elvidge CD, Alley RE (1991) An evaluation of techniques for the extraction of mineral absorption features from high spectral resolution remote sensing data.
Photogrammetric Engineering and Remote Sensing 57(10): 1303-1309
Richards JA, Jia X (1999) Remote sensing digital image analysis: an introduction. SpringerVerlag, Berlin
Roberts RS (2000) Characterization of hyperspectral data using a genetic algorithm. Proceedings of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers
1, pp 169-173
Rosenfeld GH, Fitzpatrick-Lins K (1986) A coefficient of agreement as a measure of thematic
classification accuracy. Photogrammetric Engineering and Remote Sensing 52: 223-227
Saha AK, Arora MK, Csaplovics E, Gupta RP (2004) Land cover classification using IRS lC
LISS and topographic data in a rugged terrain in Himalayas. Geo Carto International
(Revision sent)
Schalkoff RJ (1997) Artificial neural networks. McGraw-Hill, New York
Settle JJ, Drake NA (1993) Linear mixing and the estimation of ground cover proportions.
International Journal of Remote Sensing 14: 1159-1177
Simone G, Farina A, Morabito FC, Serpico SB, Bruzzone L (2002) Image fusion techniques
for remote sensing applications. Information Fusion 3: 3-15
Smith GM, Milton EJ (1999) The use of the empirical line method to calibrate remotely
sensed data to reflectance. International Journal of Remote Sensing 20: 2653-2662
Stehman SV (1997) Selecting and interpreting measures of thematic classification accuracy.
Remote Sensing of the Environment 62: 77-89
Stehman SV (1999) Basic probability sampling designs for thematic map accuracy assessment. International Journal of Remote Sensing 20: 2423-2441
Story M, Congalton RG (1986) Accuracy assessment: a user's perspective. Remote Sensing
of the Environment 52(3): 397-399
Swain PH, Davis SM (eds) (1978) Remote sensing: the quantitative approach, McGraw Hill,
New York
Ullman RE (1999) HDF-EOS, NASA's standard data product distribution format for the
Earth Observing System data information system. Proceedings of the IEEE International
Geoscience and Remote Sensing Symposium 1, pp 276-278
Varshney PK, Chen H, Ramac LC, Uner M, Ferris D, Alford M (1999) Registration and fusion
of infrared and millimeter wave images for concealed weapon detection. Proceedings
of the IEEE International Conference on Image Processing 3, pp 532-536
Yu X, HoffLE, Reed IS, Chen AM, Stotts LB (1997) Automatic target detection and recognition in multiband imagery: a unified ML detection and estimation approach. IEEE
Transactions on Image Processing 6(1): 143-156
Zhang Z, Blum RS (1999) A categorization and study of multiscale-decomposition-based
image fusion schemes. Proceedings of the IEEE, pp 1315-1328
Zitova B, Flusser J (2003) Image registration methods: a survey. Image and Vision Computing, pp 977-1000