Selected Publications - David Landgrebe

Following is a list of publications relevant to the field of remote sensing. Several which are of more current interest are available for downloading and view of the full paper. These are in Adobe Acrobat format and require the Acrobat Reader software, which is available for downloading without cost for many different platforms.

A. Research Book Contributions and Books Published

[1] D. A. Landgrebe and F. C. Billingsly, "Computer Processing of Images in Remote Sensing Applications," Chapter in American Society of Photogrammetry Manual of Remote Sensing (1st edition), 1974.

[2] D. A. Landgrebe, "Data Processing for Remote Sensing," Chapter 8 of Remote Sensing of Environment, Academic Press, 1976.

[3] D. A. Landgrebe, co-author, Remote Sensing: The Quantitative Approach, McGraw-Hill International Book Company, 1978.

[4] James C. Tilton, David A. Landgrebe, and Robert A. Schowengerdt, "Information Processing For Remote Sensing," A chapter in Encyclopedia of Electrical and Electronics Engineering, Wiley, 1999.

[5] David Landgrebe, Information Extraction Principles and Methods for Multispectral and Hyperspectral Image Data, Chapter 1 of Information Processing for Remote Sensing, edited by C. H. Chen, published by the World Scientific Publishing Co., Inc., 1060 Main Street, River Edge, NJ 07661, USA, 2000

[6] David Landgrebe, "Analysis of Multispectral and Hyperspectral Image Data," Chapter 10 of Photogrammetry by Edward M. Mikhail, James S. Bethel, and J. Chris McGlone, Wiley, 2001.

[7] David Landgrebe, Signal Theory Methods in Multispectral Remote Sensing, John Wiley and Sons, 508 pages plus a CD, 2003.

    B. Journal Papers

[1] K. S. Fu, D. A. Landgrebe, and T. L. Phillips, "Information Processing of Remotely Sensed Agricultural Data," Proceedings of the IEEE, Vol. 57, No. 4, pp. 639-653, April 1969.

[2] R. L. Kettig and D. A. Landgrebe, "Computer Classification of Remotely Sensed Multispectral Image Data by Extraction and Classification of Homogeneous Objects," IEEE Transactions on Geoscience Electronics, Volume GE-14, No. 1, pp. 19-26, January 1976.

[3] David S. Moore, Stephen J. Whitsitt, and David A. Landgrebe, "Variance Comparisons for Unbiased Estimators of Probabilities of Correct Classifications," IEEE Transaction on Information Theory, Vol. IT-22, No. 1, pp. 102-105, January 1976.

[4] D. J. Wiersma and D. A. Landgrebe, "Analytical Design of Multispectral Sensors," IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-18, No. 2, pp. 180-189, 1980.

[5] D.A. Landgrebe, "The Development of a Spectral-Spatial Classifier for Earth Observational Data," Pattern Recognition, Vol. 12, No. 3, pp. 165-175,1980.

[6] J. A. Richards, D. A. Landgrebe and P. H. Swain, "Pixel Labeling by Supervised Probabilistic Relaxation," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-3, No. 2, pp. 188-191 March 1981.

[7] J. A. Richards, D. A. Landgrebe and P. H. Swain, "On the Accuracy of Pixel Relaxation Labeling," IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-11, No. 4, pp. 303-309, April 1981.

[8] D. A. Landgrebe, "Analysis Technology for Land Remote Sensing," Proceedings of the IEEE, Vol. 69, No. 5, pp. 628-642, May 1981.

[9] D. A. Landgrebe and P. Swain, "Characterization and Extraction of Information in Earth Observational Image Data," Proceedings of the IREE (Australia), Invited Paper, Vol. 1, No. 2, pp. 108-116, June 1981.

[10] J. A. Richards, D. A. Landgrebe, and P. H. Swain, "Supervised Pixel Relaxation Labeling as a Means for Utilizing Ancillary Information in the Classification of Remote Sensing Image Data," Remote Sensing of Environment, Volume 12, pp. 463-477, 1982.

[11] D. A. Landgrebe, "Land Observational Sensors in Perspective," Remote Sensing of Environment, Invited Paper, Vol. 13, No. 5, pp. 391-402, October 1983.

[12] H. M. Kalayeh, M. J. Muasher, and D. A. Landgrebe, "Feature Selection When Limited Numbers of Training Samples are Available," IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-21, No. 4, pp. 434-438, Oct. 1983.

[13] M. J. Muasher and D. A. Landgrebe, "The K-L Expansion as an Effective Feature Ordering Technique for Limited Training Sample Size," IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-21, No. 4, pp. 438-441, Oct. 1983.

[14] H. M. Kalayeh, D. A. Landgrebe, "Predicting the Required Number of Training Samples," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-5, No. 6. pp 664-666, Nov. 1983.

[15] H. M. Kalayeh and D. A. Landgrebe, "Adaptive Relaxation Labeling," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-6, No. 3, pp. 369-372, May 1984.

[16] M. J. Muasher and D. A. Landgrebe, "A Binary Tree Feature Selection Technique for Limited Training Set Size," Remote Sensing of Environment, Vol. 16, No. 3, pp 183-194, December 1984.

[17] D.A. Landgrebe and E.R. Malaret, "Noise in Remote Sensing Systems: Effect on Classification Accuracy," IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-24, No. 2, pp 294-299, March 1986

[18] H.M. Kalayeh and D.A. Landgrebe, "Utilizing Multitemporal Data by a Stochastic Model", IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-24, No. 5, pp 792-795, September 1986.

[19] H.M Kalayeh and D.A. Landgrebe, "Stochastic Model Utilizing Spectral and Spatial Characteristics", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-9, No. 3, pp 457-61, May 1987.

[20] C.C. Thomas Chen and David A. Landgrebe, "A Spectral Feature Design System For The HIRIS/MODIS Era," IEEE Transactions on Geoscience and Remote Sensing, Vol. 27, No. 6, pp 681-686, November 1989.

[21] Kerekes, John P. and David A. Landgrebe, "Simulation of Optical Remote Sensing Systems," IEEE Transactions on Geoscience and Remote Sensing, Vol. 27, No. 6, Nov. 1989, pp. 762-771

[23] Kerekes, J.P. and D.A. Landgrebe, "Parameter Tradeoffs for Imaging Spectroscopy Systems," IEEE Transactions on Geoscience and Remote Sensing, Vol. 29, No. 1, Jan-91, pp 57-65.

[24] Kerekes, J.P. and D.A. Landgrebe, "An Analytical Model of Earth Observational Remote Sensing Systems," IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, No. 1, Jan-91, pp 125-133.

[25] Lee, Chulhee and David A. Landgrebe, "Fast Multistage Likelihood Classification," IEEE Transactions on Geoscience and Remote Sensing, Vol. 29, No. 4, July 1991, pp 509-517.

[26] Kim, B. and D.A. Landgrebe, "Hierarchical Classifier Design in High Dimensional, Numerous Class Cases," IEEE Transactions on Geoscience and Remote Sensing, Vol. 29, No. 4, July 1991, pp 518-528.

[27] Safavian, S. Rasoul and David A. Landgrebe, "A Survey of Decision Tree Classifier Methodology," IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, No. 3, pp 660-674, May 1991.

[28] Byeungwoo Jeon and D. A. Landgrebe, "Classification with Spatio-Temporal Interpixel Class Dependency Contexts," IEEE Transactions on Geoscience and Remote Sensing, Vol. 30, No. 4, July 1992, pp 663-672.

[29] Chulhee Lee and David A. Landgrebe, "Decision Boundary Feature Extraction for Non-Parametric Classification," IEEE Transactions on System, Man, and Cybernetics, Vol. 23, No. 2, March/April, 1993, pp 433-444.

[30] Chulhee Lee and David A. Landgrebe, "Feature Extraction Based On Decision Boundaries," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 4, April 1993, pp 388-400.

[31] Chulhee Lee and David A. Landgrebe, "Analyzing High Dimensional Multispectral Data," IEEE Transactions on Geoscience and Remote Sensing, Volume 31, No. 4, pp 792-800, July 1993.

[32] Byeungwoo Jeon and David A. Landgrebe, "Fast Parzen Density Estimation Using Clustering-Based Branch and Bound," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 9, pp 950-954, September 1994.

[33] Behzad M. Shahshahani and David A. Landgrebe, "The Effect of Unlabeled Samples in Reducing the Small Sample Size Problem and Mitigating the Hughes Phenomenon," IEEE Transactions on Geoscience and Remote Sensing, Vol. 32, No. 5, pp 1087-1095, September 1994.

[34] Hoffbeck, Joseph P. and David A. Landgrebe, "Covariance Matrix Estimation and Classification with Limited Training Data," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, no. 7, pp. 763-767, July 1996.

[35] Hoffbeck, Joseph P. and David A. Landgrebe, "Classification of Remote Sensing Images having High Spectral Resolution," Remote Sensing of Environment, Vol. 57, No. 3, pp 119-126, September 1996.

[36] Chulhee Lee and David A. Landgrebe, "Decision Boundary Feature Extraction for Neural Networks," IEEE Transactions on Neural Networks, Vol 8. No. 1, pp. 75-83, January 1997.

[37] Landgrebe, David, "The Evolution of Landsat Data Analysis," Photogrammetric Engineering and Remote Sensing, Vol. LXIII, No. 7, July 1997, pp. 859-867.

[38] Jimenez, Luis, and David Landgrebe, "Supervised Classification in High Dimensional Space: Geometrical, Statistical, and Asymptotical Properties of Multivariate Data," IEEE Transactions on System, Man, and Cybernetics, Volume 28, Part C, No. 1, pp. 39-54, February 1998.

[39] Byeungwoo Jeon and David Landgrebe, "Partially Supervised Classification Using Weighted Unsupervised Clustering," IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No.2, pp 1073-1079, March 1999.

[40] Byeungwoo Jeon and David Landgrebe, "Decision Fusion Approach To Multitemporal Classification," IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, Volume 37, No. 3, pp 1227-1233, May 1999.

[41] Saldju Tadjudin and David Landgrebe, "Covariance Estimation With Limited Training Samples," IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 4, pp. 2113-2118, July 1999.

[42] Victor Haertel and David Landgrebe, "On the Classification of Classes with Nearly Equal Spectral Responses in Remote Sensing Hyperspectral Image Data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 5, Part 2, pp. 2374-2386, September 1999.

[43] Jimenez, Luis, and David Landgrebe, "Hyperspectral Data Analysis and Feature Reduction Via Projection Pursuit, "IEEE Transactions on Geoscience and Remote Sensing. Vol. 37, No. 6, pp. 2653-2667, November 1999.

[44] Saldju Tadjudin and David A. Landgrebe, "Robust Parameter Estimation for Mixture Model," IEEE Transactions on Geoscience and Remote Sensing. Vol. 38, No. 1, pp.439-445, January 2000.

[45] Jackson, Q. and David A. Landgrebe, "An Adaptive Classifier Design for High-Dimensional Data Analysis with a Limited Training Data Set," IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, No. 12, pp. 2664-2679, December 2001.

[46] David Landgrebe, "Hyperspectral Image Data Analysis as a High Dimensional Signal Processing Problem," (Invited), Special Issue of the IEEE Signal Processing Magazine, Vol 19, No. 1 pp. 17-28, January 2002.

[47] Varun Madhok and David A. Landgrebe, "A Process Model for Remote Sensing Data Analysis," IEEE Transactions on Geoscience and Remote Sensing. Vol. 40, No. 3, pp 680-686, March 2002.

[48] Bor-Chen Kuo and David A. Landgrebe, "A Covariance Estimator for Small Sample Size Classification Problems
and Its Application to Feature Extraction,"IEEE Transactions on Geoscience and Remote Sensing, Vol. 40, No. 4, pp 814-819, April 2002.

[49] Qiong Jackson and David Landgrebe, "An Adaptive Method for Combined Covariance Estimation and Classification," IEEE Transactions on Geoscience and Remote Sensing. Volume 40, No. 5, pp 1082-1087, May 2002.

[50] Qiong Jackson and David Landgrebe, "Adaptive Bayesian Contextural Classification Based on Markov Random Fields," IEEE Transactions on Geoscience and Remote Sensing, Volume 40, No. 11, pp 2454-2463, November 2002.

[51] Bor-Chen Kuo and David Landgrebe, "A Robust Clasification Procedure Based on Mixed Classifiers and Nonparametric Weighted Feature Extraction," IEEE Transactions on Geoscience and Remote Sensing, Volume 40, No. 11, pp 2486 -2494, November 2002.

[52] M. Murat Dundar and David Landgrebe, "A Model Based Mixture Supervised Classification Approach in Hyperspectral Data Analysis," IEEE Transactions on Geoscience and Remote Sensing, Volume 40, No. 11, pp 269 -2699, December 2002.

[53] Murat Dundar and David Landgrebe, "A Cost-effective Semi-supervised Classifier Approach with Kernels," IEEE Transactions on Geoscience and Remote Sensing, Volume 42, No. 1, pp 264-270, January, 2004.

[54] M. Murat Dundar and David Landgrebe, "Toward an Optimal Supervised Classifier for the Analysis of Hyperspectral Data," IEEE Transactions on Geoscience and Remote Sensing, Volume 42, No. 1, pp 271-277, January, 2004.

[55] Bor-chen Kuo and David Landgrebe, "Nonparametric Weighted Feature Extraction for Classification," IEEE Transactions on Geoscience and Remote Sensing, Volume 42, No. 5, pp 1096-1105, May, 2004

[56] David Landgrebe, "Multispectral Land Sensing; Where From, Where To?," IEEE Transactions on Geoscience and Remote Sensing, Volume 43, No. 3, March 2005.
 

C. Conference Papers

[1] Safavian, S. Rasoul and David A. Landgrebe, "Use of Robust Estimators in Parametric Classifiers," 1989 IEEE International Conference on Systems, Man, and Cybernetics, Cambridge, MA, Vol. 1, Nov-89, pp 356-7

[2] Jeon, Byeungwoo and David A. Landgrebe, "A New Supervised Absolute Classifier," Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Washington, D.C, May-90, pp. 2363-2366

[3] Kim, B. and D.A. Landgrebe, "Hierarchical Classification in High Dimensional, Numerous Class Cases," Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Washington, D.C., May-90, pp. 2359-2362

[4] Kim, B. and D.A. Landgrebe, "Prediction of Optimal Number of Features," Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Washington, D.C., May-90, pp. 2393-2396

[5] Safavian, S. Rasoul and David A. Landgrebe, "Predictive Density Approach to Parametric Classification," Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Washington, D.C., May-90, pp. 2367-2370

[6] Jeon, Byeungwoo and David A. Landgrebe, "Spatio-Temporal Contextual Classification of Remotely Sensed Multispectral Data," Proceedings of the 1990 IEEE International Conference on Systems, Man, and Cybernetics, Los Angeles, CA, Nov-90.

[7] Byeungwoo Jeon and David A. Landgrebe, "Absolute Classification with Unsupervised Clustering," International Geoscience and Remote Sensing Symposium (IGARSS'92), Houston, TX, May 26-29, 1992, pp. 1609-1611.

[8] Chulhee Lee, Jon A. Benediktsson, and David A. Landgrebe, "Feature Selection For Neural Networks Using A Parzen Density Estimator, " International Geoscience and Remote Sensing Symposium (IGARSS'92), Houston, TX, May 26-29, 1992.

[9] B.M. Shahshahani, D.A. Landgrebe, "On the Asymptotic Improvement of Supervised Learning by Utilizing Additional Unlabeled Samples; Normal Mixture Density Case," SPIE Int. Conf. Neural and Stochastic Methods in Image and Signal Processing, San Diego, CA, July 19-24, 1992.

[10] Chulhee Lee and David A. Landgrebe, "Decision Boundary Feature Extraction for Neural Networks," IEEE International Conference on Systems Man and Cybernetics, Chicago, Ill., October 18-21, pp. 1053-1058, 1992.

[11] Byeungwoo Jeon and David A. Landgrebe, "Decision Fusion with Reliabilities in Multisource Data Classification" IEEE International Conference on Systems Man and Cybernetics, Chicago, Ill., October 18-21, pp. 617-622, 1992.

[12] David A. Landgrebe, "Hyperspectral Data Analysis Procedures with Reduced Sensitivity to Noise," Proceedings of the Workshop on Atmospheric Correction of Landsat Imagery, pp 172-176, Torrance California, June 29 - July 1, 1993.

[13] Behzad M. Shahshahani and David A. Landgrebe, "An Algorithm for Classification of Multi-Spectral Data and Its Implementation on a Massively Parallel Computer," SPIE International Symposium on Optical Applied Science and Engineering, San Diego, CA, July 11-July 16, 1993.

[14] Behzad M. Shahshahani and David A. Landgrebe, "Use Of Unlabeled Samples For Mitigating The Hughes Phenomenon," Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS'93), Tokyo, pp 1535-7, August 1993.

[15] Byeungwoo Jeon And David A. Landgrebe, "Partially Supervised Classification With Optimal Significance Testing," Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS'93), Tokyo, pp 1370-2, August 1993.

[16] David A. Landgrebe, "A Perspective on the Analysis of Hyperspectral Data," Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS'93), Tokyo, pp 1362-4, August 1993.

[17] Hoffbeck, Joseph P. and David A. Landgrebe, "Classification of High Dimensional Multispectral Image Data," Fourth Annual JPL Airborne Geoscience Workshop, Arlington, Virginia, October 25-29, 1993.

[18] Joe Hoffbeck and David A. Landgrebe, "Effect Of Radiance-To-Reflectance Transformation And Atmosphere Removal On Maximum Likelihood Classification Accuracy Of High-Dimensional Remote Sensing Data," Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS'94), CD-ROM pp 3289-3294, Pasadena, Calif, August 8-12,1994.

[19] Luis Jimenez and David Landgrebe, "High Dimensional Feature Reduction Via Projection Pursuit," Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS'94),CD-ROM pp 1473-1479, Pasadena, Calif, August 8-12,1994.

[20] Luis Jimenez and David Landgrebe, "Projection Pursuit For High Dimensional Feature Reduction: Parallel And Sequential Approaches," Presented at the International Geoscience and Remote Sensing Symposium (IGARSS'95), Florence Italy, July 10-14, 1995.

[21] David Landgrebe, "Multispectral Data Analysis: An Overview - Past, Present, and Future", Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS'95), Florence Italy, July 10-14, 1995.

[22] Luis Jimenez and David Landgrebe, "Projection Pursuit in High Dimensional Data Reduction: Initial Conditions, Feature Selection and the Assumption of Normality," IEEE International Conference on Systems, Man, and Cybernetics, Vancouver, Canada, October 22-25, 1995.

[23] Xiuping Jia and David Landgrebe, "Large Area Classification For Hyperspectral Data Sets," 8th Australasian Remote Sensing Conference, Canberra, Australia, 25-29 March, 1996.

[24] Saldju Tadjudin and David A. Landgrebe, "A Decision Tree Classifier Design For High-Dimensional Data With Limited Training Samples," Proceedings of the IGARSS 96 Symposium, Lincoln, NE, pp 790-793, 27-31 May, 1996.

[25] Pifuei Hsieh and David A. Landgrebe, "Automated Training Sample Labeling Using Laboratory Spectra," Proceedings of the IGARSS '96 Symposium, Lincoln, NE, pp 1855-1859, 27-31 May, 1996.

[26] J.A. Benediktsson, Kolbeinn Arnason, Arni Hjartarson, and David Landgrebe, "Classification And Feature Extraction Based On Enhanced Statistics," Proceedings of the IGARSS 96 Symposium, Lincoln, NE, pp 414-416, 27-31 May, 1996.

[27] David A. Landgrebe, "On the Information Content of Optical Land Remotely Sensed Data," (Invited), Progress In Electromagnetics Research Symposium, Innsbruck Austria, July 8-12, 1996.

[28] Biehl, L. and David Landgrebe, "MultiSpec - A Tool for Multispectral-Hyperspectral Image Data Analysis," 13th Pecora Symposium, Sioux Falls, SD, August 20-22, 1996.

[29] David A. Landgrebe, "On Progress Toward Information Extraction Methods for Hyperspectral Data," SPIE 42nd Annual Meeting, San Diego CA July 27-August 1, 1997.

[30] Saldju Tadjudin and David A. Landgrebe, "Robust Parameter Estimation For Mixture Model," IEEE International Geoscience and Remote Sensing Symposium, Seattle, WA July 6-10, 1998.

[31] Saldju Tadjudin and David A. Landgrebe, "Covariance Estimation For Limited Training Samples,"IEEE International Geoscience and Remote Sensing Symposium, Seattle, WA July 6-10, 1998.

[32] Pi-Fuei Hsieh and David Landgrebe, "Linear Feature Extraction for Multiclass Problems," IEEE International Geoscience and Remote Sensing Symposium, Seattle, WA July 6-10, 1998.

[33] Pi-Fuei Hsieh and David Landgrebe, "Lowpass Filter For Increasing Class Separability," IEEE International Geoscience and Remote Sensing Symposium, Seattle, WA July 6-10, 1998.

[34] Pi-Fuei Hsieh and David Landgrebe, "Statistics Enhancement In Hyperspectral Data Analysis Using Spectral-Spatial Labeling, The EM Algorithm, And The Leave-One-Out Covariance Estimator," SPIE International Symposium on Optical Science, Engineering, and Instrumentation, San Diego, CA, July 19-24, 1988.

[35] David Landgrebe, "Some Fundamentals and Methods for Hyperspectral Image Data Analysis," SPIE International Symposium on Biomedical Optics (Photonics West), San Jose California, January 23-29, 1999.

[36] Varun Madhok and David Landgrebe, "Supplementing Hyperspectral Datawith Digital Elevation," Proceedings of the International Geoscience and Remote Sensing Symposium, Hamburg, Germany, June 28 - July 2, 1999.

[37] David Landgrebe, "On Information Extraction Principles for Hyperspectral Data," 4th International Conference on GeoComputation, Fredericksburg, Virginia, USA, 25-28 July, 1999.

[38] James Bethel, Changno Lee, and David Landgrebe, "Geometric Registration and Classification of Hyperspectral Airborne Pushbroom Data," 19th International Symposium on Photogrammetry and Remote Sensing, Amsterdam, The Netherlands, 16-23 July 2000.

[39] Larry Biehl and David Landgrebe, "Effect of the Number of Samples Used in a Leave-One-Out Covariance Estimator," SPIE International Symposium on Aerosense, Orlando Florida, 24-28 April, 2000.

[40] David Landgrebe, "On the Relationship Between Class Definition Precision and Classification Accuracy in Hyperspectral Analysis," Proeedings of the International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, July 24-28, 2000.

[41] Hassan Ghassemian and David Landgrebe, "Multispectral Image Compression by an On-Board Scene Segmentation," Proeedings of the International Geoscience and Remote Sensing Symposium, Sydney Australia, July 9-13, 2001.

[42] Qiong Jackson and David Landgrebe, "A Self-Improving Classifier Design for High-Dimensional Data Analysis with a Limited Training Data Set," Proeedings of the International Geoscience and Remote Sensing Symposium, Sydney Australia, July 9-13, 2001. See also item B[45] above.

[43] David Landgrebe, "Toward a maximally effective means for analysis of hyperspectral data," Proceedings of the SPIE International Symposium on Remote Sensing, Toulouse, France, September 17-21, 2001.

[44] Bor-Chen Kuo and David A. Landgrebe "Hyperspectral Data Classification Using Nonparametric Weighted Feature Extraction," International Geoscience and Remote Sensing Symposium, Toronto, Canada, June 24-28, 2002.

[45] Bor-Chen Kuo and David A. Landgrebe "Regularized Covariance Estimators for Hyperspectral Data Classification and Its Application to Feature Extraction," International Geoscience and Remote Sensing Symposium, Toronto, Canada, June 24-28, 2002.

[46] Qiong Jackson and David Landgrebe, "Adaptive Bayesian Contextual Classification Based on Markov Random Fields," International Geoscience and Remote Sensing Symposium, Toronto, Canada, June 24-28, 2002

D. Theses/Technical Reports

[1] John Kerekes and David Landgrebe, "HIRIS Performance Study," Technical Report TR-EE 89-23, Purdue School of Electrical Engineering, April 1989.

[2] John Kerekes and David Landgrebe, "RSSIM: A Simulation Program for Optical Remote Sensing Systems," Technical Report TR-EE 89-48, Purdue School of Electrical Engineering, August 1989.

[3] John Kerekes and David Landgrebe "Modeling, Simulation, and Analysis of Optical Remote Sensing Systems," (PhD Thesis) Technical Report TR-EE 89-49, Purdue School of Electrical Engineering, August 1989.

[4]Safavian, S. Rasoul and D. Landgrebe, "Topics in Inference and Decision-Making with Partial Knowledge," Technical Report TR-EE 90-53, Purdue University, Sep-90, 45 pp

[5] Chulhee Lee and David Landgrebe, "Feature Extraction and Classification Algorithm For High Dimensional Data, " PhD Thesis and School of Electrical Engineering Technical Report TR-EE 93-1, January, 1993 (222 pages).

[6] Byeungwoo Jeon and David A. Landgrebe, "Design of Partially Supervised Classifiers for Multispectral Image Data," School of Electrical Engineering Technical Report TR-EE 93-11, March 1993.

[7] Behzad Shahshahani and David Landgrebe, "Classification of Multispectral Data by Joint Supervised-Unsupervised Learning," PhD Thesis and School of Electrical Engineering Technical Report TR-EE 94-1, January 1994.

[8] Joseph P. Hoffbeck and David Landgrebe, "Classification of High Dimensional Multispectral Data," PhD Thesis and School of Electrical Engineering Technical Report TR-EE 95-14, May 1995.

[9] Luis Jimenez and David Landgrebe, "High Dimensional Feature Reduction Via Projection Pursuit," PhD Thesis and School of Electrical & Computer Engineering Technical Report TR-ECE 96-5, April 1996.

[10] Pi-Fuei Hsieh and David Landgrebe, "Classification Of High Dimensional Data," PhD Thesis and School of Electrical & Computer Engineering Technical Report TR-ECE 98-4, May 1998 (121 pages)

[11] Saldju Tadjudin and David Landgrebe, "Classification of High Dimensional Data with Limited Training Samples," PhD Thesis and School of Electrical & Computer Engineering Technical Report TR-ECE 98-8, May 1998 (123 pages).

[12] Varun Madhok and David Landgrebe, "Spectral-Spatial Analysis of Remote Sensing Data: An Image Model and A Procedural Design," PhD Thesis and School of Electrical & Computer Engineering Technical Report TR-ECE 99-10, August 1999 (162 pages).

[13] Qiong Zhang Jackson and David Landgrebe, Design Of An Adaptive Classification Procedure For The Analysis Of High-Dimensional Data With Limited Training Samples, PhD Thesis and School of Electrical & Computer Engineering Technical Report TR-ECE 01-5, December 2001 (137 pages).

[14] Bor-Chen Kuo and David Landgrebe, Improved Statistics Estimation And Feature Extraction For Hyperspectral Data Classification, PhD Thesis and School of Electrical & Computer Engineering Technical Report TR-ECE 01-6, December 2001 (88 pages).

[15] Mehmet M. Dundar and David Landgrebe, Toward An Optimal Analysis of Hyperspectral Data, PhD Thesis and School of Electrical & Computer Engineering Technical Report TR-ECE 03-07 May 2003 (94 pages).
 



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