3. Journal Publications

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Last updated: Oct 04, 2018 by Chia-Chen Liang
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REFEREED JOURNAL PUBLICATIONS

2018 (7)

  1. C. Yu, M. Song, and C.-I. Chang, “Band Subset Selection for Hyperspectral Image Classification,” Remote Sensing, vol. 10, no. 1, p. 113, Jan. 2018.

  2. C.-I Chang, "Spectral Inter-Band Discrimination Capacity of Hyperspectral Imagery," in IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 3, pp. 1749-1766, March 2018. doi: 10.1109/TGRS.2017.2767903
  3. J. Lei, Y. Li, D. Zhao, J. Xie, C.-I. Chang, L. Wu, X. Li, J. Zhang, and W. Li, “A Deep Pipelined Implementation of Hyperspectral Target Detection Algorithm on FPGA Using HLS,” Remote Sensing, vol. 10, no. 4, p. 516, Mar. 2018.
  4. C.-I Chang, "A Review of Virtual Dimensionality for Hyperspectral Imagery," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 4, pp. 1285-1305, April 2018. doi: 10.1109/JSTARS.2017.2782706
  5. C. Yu, B. Xue, M. Song, Y. Wang, S. Li and C.-I Chang, "Iterative Target-Constrained Interference-Minimized Classifier for Hyperspectral Classification," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 4, pp. 1095-1117, April 2018. doi: 10.1109/JSTARS.2018.2802041
  6. C. Yu, L.-C. Lee, C.-I Chang, B. Xue, M. Song and J. Chen, "Band-Specified Virtual Dimensionality for Band Selection: An Orthogonal Subspace Projection Approach," in IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 5, pp. 2822-2832, May 2018. doi: 10.1109/TGRS.2017.2784372
  7. Y. Wang, L.-C. Lee, B. Xue, L. Wang, M. Song, C. Yu, S. Li and C.-I Chang, "A Posteriori Hyperspectral Anomaly Detection for Unlabeled Classification," in IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 6, pp. 3091-3106, June 2018. doi: 10.1109/TGRS.2018.2790583

2017 (9)

  1. C.-I Chang, H.C. Li , C.C. Wu and M. Song, “Recursive geometric simplex growing analysis for finding endmembers in hyperspectral imagery,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 10, no. 1, pp. 296-308, January 2017.

  2. Z. Dezman, C. Gao, S. Yang, P. Hu, Y. Li, H.-C. Li, C.-I Chang and C. Mackenzie, “Anomaly detection outperforms logistic regression in predicting outcomes in trauma patients,” Prehospital Emergency Care, vol. 21, no. 2, pp. 174-179, 2017.

  3. C. I. Chang, "Adaptive Linear Spectral Mixture Analysis," in IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 3, pp. 1240-1253, March 2017. doi: 10.1109/TGRS.2016.2620494

  4. L. Wang, C. I Chang, L.C. Lee, Y. Wang, B. Xue, M. Song, C. Yu and S. Li, "Band Subset Selection for Anomaly Detection in Hyperspectral Imagery," in IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 9, pp. 4887-4898, Sept. 2017. doi: 10.1109/TGRS.2017.2681278

  5. B. Xue, C. Yu, Y. Wang, M. Song, S. Li, L. Wang, H.-M. Cheng and C. -I Chang, "A Subpixel Target Detection Approach to Hyperspectral Image Classification," in IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 9, pp. 5093-5114, Sept. 2017. doi: 10.1109/TGRS.2017.2702197
  6. C.-I Chang, Y. Li and Y. Wang, "Progressive Band Processing of Fast Iterative Pixel Purity Index for Finding Endmembers," in IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 9, pp. 1464-1468, Sept. 2017. doi: 10.1109/LGRS.2017.2710219
  7. C. I Chang, L. -C. Li, B. Xue, M. Song and J. Chen, "Channel Capacity Approach to Hyperspectral Band Subset Selection," in IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 10, no. 10, pp. 4630-4644, October, 2017.
  8. L. Wang, H. Li, B. Xue and C. Chang, "Constrained Band Subset Selection for Hyperspectral Imagery," in IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 11, pp. 2032-2036, Nov. 2017. doi: 10.1109/LGRS.2017.2749209
  9. H.-M. Chen, H. Wang, J.-W. Chai, C.-C. Chen, B. Xue, L. Wang, C. Yu, Y. Wang, M. Song, and C.-I. Chang, “A Hyperspectral Imaging Approach to White Matter Hyperintensities Detection in Brain Magnetic Resonance Images,” Remote Sensing, vol. 9, no. 11, p. 1174, 2017.

2016 (6)

  1. H.C. Li, C.-I Chang and M. Song, “Progressive band processing of orthogonal subspace projection,” IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 1, pp. 3-7, January 2016. 
  2. C.-I Chang, W. Xiongand S.Y. Chen, “Convex cone volume analysis for finding endmembers in hyperspectral imagery,” Int. J. of Computational Science and Engineering, vol. 12, nos. 2/3, pp. 209-236, 2016. 
  3. A. H. Kashani, M. Wong, N. Koulisis, C.-I Chang, G.l. Martin, M.S. Humayun, “Hyperspectral imaging of retinal microvascular anatomy,” Journal of Biomedical Engineering and Informatics, vol. 2, no. 1, pp. 139-150, 2016. 
  4. H.-C. Li and C.-I Chang, “Recursive orthogonal projection-based simplex growing algorithm,” IEEE Trans. on Geoscience and Remote Sensing, vol. 54, no. 7, pp. 3780-3793, July 2016. DOI 10.1109/TGRS.2016.2527737. 
  5. C.-I Chang and Y. Li, “Recursive band processing of automatic target generation process for subpixel detection in hyperspectral imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 54, no. 9,  pp. 5081-5094, September, 2016. 
  6. C.-I Chang, S.Y. Chen, H.C. Li and C.-H. Wen, “A comparative analysis among ATGP, VCA and SGA for finding endmembers in hyperspectral imagery,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 9, no. 9, pp. 4280-4306, September, 2016. 

2015 (12)

  1. C.-I Chang, R. Schultz, M. Hobbs, S.-Y. Chen, Y. Wang and C. Liu, “Progressive band processing of constrained energy minimization,” IEEE Trans. on Geoscience and Remote Sensing, vol. 53, no. 3, pp. 1626-1637, March, 2015. 
  2. M.-P. Song and C.-I Chang, “A theory of recuresive orthogonal subspace projection for hyperspectral imaging,” IEEE Trans. on Geoscience and Remote Sensing, vol. 53, no. 6, pp. 3055-3072, 2015. 
  3. C.-I Chang, C.C. Wu, K.H. Liu, H.M. Chen, C.C.C. Chen and C.H. Wen, “Progressive band processing of linear spectral unmiixng for hyperspectral imagery,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 8, no. 7, pp. 2583-2597, 2015.
  4. C.-I Chang and C.C. Wu, “Design and development of iterative pixel purity index,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 8, no. 6, pp. 2676-2695, June, 2015. 
  5. C.-I Chang, Y. Li, M. Hobbs, R. Schultz and W.M. Liu, “Progressive band processing of anomaly detection,“ IEEE Journal of Selected Topics in Signal Processing, vol. 8, no. 7, pp. 3558-3571, 2015. 
  6. C.-I Chang, Y. Wang and S.Y. Chen, “Anomaly detection using causal sliding windows,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 8, no. 7, pp. 3260-3270, 2015. 
  7. C. Lin, S. Popescu; G. Thomson; K. Tsogt, C.-I Chang. "Classification of tree species in overstorey canopy of subtropical forest using QuickBird images," PLoS ONE 10(5): e0125554. doi:10.1371/journal.pone.0125554, 2015. 
  8. C.-I Chang, H.C. Li, M. Song, C. Liu and L.F. Zhang, “Real-time constrained energy minimization for subpixel detection,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 8, no. 6, pp. 2545-2559, 2015.
  9. M.P. Song, S.-Y. Chen, H.C. Li, H.M. Chen, C.C.C. Chen and C.-I Chang, “Finding virtual signatures for linear spectral unmixing,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 8, no. 6, pp. 2704-2719, 2015.
  10. C.-I Chang, C. Gao and S.Y. Chen, “Recursive automatic target generation process,” IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 9, pp. 1848-1852, Sep. 2015. 
  11. Y.C. Chiou, C.C.C. Chen, S.Y. Chen, H.M. Chen, J.W. Chai, Y.C. Ouyang, O-C. Su, C.W. Yang, S.K. Lee and C.-I Chang, “Magnetic resonance brain tissue classification and volume calculation,” J. Chinese Institute of Engineers, vol. 38, no. 8, 2015. DOI:10.1080/02533839.2015.1056552.
  12. C. Lin, C.C. Wu, K. Tsogt, Y.C. Ouyang and C.-I Chang, “Effects of atmospheric correction and pansharpening on LULC classification accuracy using WorldView-6 imagery,” Information Processing in Agriculture, vol. 2, issue 1, pp. 25-36, May 2015. 

2014 (3)

  1. S.Y. Chen, Y. Wang, C.C. Wu, C. Liu and C.-I Chang, “Real time causal processing of anomaly detection in hyperspectral imagery,” IEEE Trans. on Aerospace and Electronics Systems, vol. 50, no. 2, pp. 1511-1534, April 2014. 
  2. C.-I Chang and K.-H. Liu, “Progressive Band Selection of Spectral Unmixing for Hyperspectral Imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 52, no. 4, pp. 2002-2017, April 2014. 
  3. C.-I Chang, W. Xiong and C.H. Wen, “A theory of high order statistics-based virtual dimensionality for hyperspectrak imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 52, no. 1, pp. 188-208, January, 2014. 10.1109/TGRS.2012.2237554. 

2013 (8)

  1. C.-I Chang, W. Xiong and C.C. Wu, “ Field-Programmable Gate Array Design of Implementing Simplex Growing Algorithm for Hyperspectral Endmember Extraction,” IEEE Trans. on Geoscience and Remote Sensing, vol. 51, no. 3, pp. 1693-1700, March 2013.
  2. W. Liu and C.-I Chang, “Multiple-Window Anomaly Detection for Hyperspectral Imagery,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 6, no. 2, pp. 664-658, April 2013. 
  3. K.H. Liu, E. Wong, C.H. Wen and C.-I Chang, “Kernel-Based Weighted Abundance Constrained Linear Spectral Mixture Analysis for Remotely Sensed Images,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 6, no. 2, pp. 531-553, April 2013. DOI: 10.1109/JSTARS.2012.2234441.
  4. H.M. Chen, C. Lin, S.Y. Chen, C.H. Wen, C.C.C. Chen, Y.C. Ouyang and C.-I Chang, “PPI-SVM-Iterative FLDA Approach to Unsupervised Multispectral Image Classification,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 6, no. 4, pp. 1834-1842, August 2013. DOI:0.1109/JSTARS.2012.2225097. 
  5. C.-I Chang, C.H. Wen and C.C. Wu, “Relationship exploration among PPI, ATGP and VCA via theoretical analysis,” Int. J. of Computational Science and Engineering, vol. 8, no. 4, pp. 361-367, 2013. 
  6. C.C. Wu and C.-I Chang, “Does A Simplex Formed by Endmembers Really Yield Maximal Volume?,” Int. J. of Computational Science and Engineering, vol. 8, no. 3, pp. 274-280, 2013. 
  7. C.-C.C. Chen, E. Wong, H.-M. Chen, S.-Y. Chen, J.-W. Chai, C. W. Yang, S. K. Lee, Y. K. Wong and C.-I Chang., “Intra-pixel multispectral processing of magnetic resonance brain images for tissue characterization,” Int. J. of Computational Science and Engineering, vol. 8, no. 2, pp. 87-110, 2013. DOI: 10.1504/IJCSE.2013.053090 
  8. G. Saiprasad, C.-I Chang, N. Safdar, N. Saenz and E. Siegel, “Adrenal gland abnormality detection using random forest classification,” J. Digital Imaging, January, 2013. DOI 10.1007/s10278-012-9554-7. 

2012 (3)

  1. C. Lin, K. Tsogt and C.-I Chang, “An Empirical Model-based Method for Signal Restoration of SWIR in ASD Field Spectroradiometry,” Photogrammetric Engineering and Remote Sensing, vol. 78, no. 2, pp. 119-127, February 2012. 
  2. K.H. Liu, E. Wong, Y. Du, C.C.C. Chen and C.-I Chang, “Kernel-Based Linear Spectral Mixture Analysis,” IEEE Geoscience and Remote Sensinbg Letters, vol. 9, no. 1, pp. 129-133, January 2012. 
  3. P.S. Liao, S.-M. Guo, N.-S. Yu, L.C. Chen, L, S.K. Lee and C.-I Chang, “Mass Detection in Mammograms,” International Journal on Computer, Comsumer and Control (IJ3C), vol. 1, no. 1, pp. 8-16, 2012.  

2011 (7)

  1. A. Plaza, C.-I Chang, S.D. Gasster, B. Huang and C.A. Lee, “ Recent developments in high performance computing for remoite sesning : a review,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 4, no. 3, pp. 508-527, September, 2011.
  2. W. Xiong, C.-C. Wu, C.-I Chang, K. Kapalkis and H.M. Chen, “Fast algorithms to implement N-FINDR for hyperspectral endmember extraction,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 4, no. 3, pp. 545-564, September, 2011.
  3. C.-I Chang, S. Wang and K.H. Liu, “Progressive band dimensionality expansion and reduction for hyperspectral imagery,” IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, vol. 4, no. 3, pp. 591-614, September, 2011.
  4. C.-I Chang, X. Jiao, Y. Du and H.M. Chen, “Component-based unsupervised linear spectral mixture analysis for hyperspectral imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4123-4137, November 2011. DOI 10.1109/TGRS.2011.2142419.
  5. C.-I Chang, W. Xiong, H.M. Chen and J.W. Chai, “Maximum orthogonal subspace projection to estimating number of spectral signal sources for hyperspectral images,” IEEE Journal of Selected Topics in Signal Processing, , vol. 5, no. 3, pp. 504-520, June 2011.
  6. C.-I Chang and H. Safavi, “Progressive dimensionality reduction by transform for hyperspectral image analysis,” Pattern Recognition, April 30, 2011, online access: doi:10.1016/j.patcog.2011.03.030 .
  7. C.-I Chang, C.-C. Wu and C.-T. Tsai, “Random N-finder algorithm,” IEEE Trans. on Image Processing, vol. 20, no. 3, pp. 641-656, March 2011.

2010 (12)

  1. K. Fisher and C.-I Chang, “Progressive band selection for satellite hyperspectral data compression and transmission,” J. Applied Remote Sensing, vol. 4, 041770 (Sep 24, 2010); doi:10.1117/1.3502036.
  2. C.-I Chang, B. Ramakishna, J. Wang and A. Plaza, “Exploitation-based hyperspectral image compression,” J. Applied Remote Sensing, vol. 4, 041760 (Dec 03, 2010); doi:10.1117/1.3530429.
  3. C.-I Chang, “Multiple-parameter receiver operating characteristic analysis for signal detection and classification,” IEEE Sensors Journal, vol. 10, no. 3, pp.423-442, March 2010. (invited paper)
  4. C.-I Chang, S. Chakravarty and C.-S. Lo, “Spectral feature probabilistic coding for hyperspectral signatures,” IEEE Sensors Journal, vol. 10, no. 3, pp.395-409, March 2010.
  5. S. Wang, C.-M. Wang, M.-L. Chang and C.-I Chang, “New applications of Kalman filtering approach to hyperspectral signature estimation, identification and abundance quantification,” IEEE Sensors Journal, vol. 10, no. 3, pp.547-563, March 2010.
  6. C.-I Chang, C.-C. Wu and H.M. Chen, “Random pixel purity index algorithm,” IEEE Trans. on Geoscience and Remote Sensing Letters, vol. 7, no. 2, pp. 324-328, April 2010.
  7. C.-I Chang, C.C. Wu, C.-S Lo and M.-L. Chang, “Real-time simplex growing algorithms for hyperspecral endmember extarction,” IEEE Trans. on Geoscience and Remote Sensing, vol. 40, no. 4, pp. 1834-1850, April, 2010.
  8. C.-I Chang, C.-C. Wu and H.M. Chen, “Real time N-finder processing algorithms,” J. Real-Time Image Processing, February 16, 2010 [DOI: 10.1007/s11554-010-0151-z].
  9. C.-I Chang, X. Jiao, Y. Du and M.-L. Chang, “A review of unsupervised hyperspectral target analysis,” EURASIP Journal on Advanced in Signal Processing, Volume 2010 (2010), Article ID 503752, 26 pages [doi:10.1155/2010/503752].
  10. C.-Y. Yu, Y.-C. Ouyang, C.-M. Wang and C.-I Chang, “Adaptive inverse hyperbolic tangent algorithm for dynamic contrast adjustment in displaying scenes,” EURASIP Journal on Advanced in Signal Processing, Volume 2010 (2010), Article ID 485151, 20 pages, [doi:10.1155/2010/485151].
  11. J.-W. Chai, H.M. Chen, C.C.C. Chen, Y.C. Ouyang, S.K. Lee and C.-I Chang “Quantitatitve analysis of brain magnetic resonance images using support vetor machine in conjunctioin with indepednent component analysis,” J. Magnetic Resonance Imaging, vol. 32, pp. 24-34, 2010. [DOI 10.1002/jmri.22210].
  12. C.-I Chang, W. Xiong, W. Liu, C.C. Wu and C.C.C. Chen, “Linear spectral mixture analysis-based approaches to estimation of virtual dimensionality in hyperspectral imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 48, no. 11, pp. 3960-3979, Nov. 2010.

2009 (3)

  1. C.-I Chang, S. Chakravarty, H. Chen and Y.C. Ouyang “Spectral derivative feature coding for hyperspectral signature,” Pattern Recognition, vol. 42, no. 3,  pp. 395-408, March 2009.
  2. B. Ramakrishna, W. Liu, G. Saiprasad, N. Safdar, C.-I Chang, K. Siddiqui, W. Kim, E. Siegel, J.W. Chai, C.C.C. Chen and S.K. Lee, “An automatic computer-aided detection system for magnetic resonance imaging of meniscus tears,” IEEE Transaction on Medical Imaging, vol. 28, no. 8, pp. 1308-1316, August 2009.
  3. C.C. Wu, C.S. Lo and C.-I Chang, “Improved process for use of a simplex growing algorithm for endmember extraction,” IEEE Trans. on Geoscience and Remote Sensing Letters, vol. 6, no. 3, pp. 523-527, July 2009.

2008 (5)

  1. Y.C. Ouyang, H.M. Chen, J.W. Chai, C.C.C. Chen, S.K. Poon, C.W. Yang, S.K. Lee and C.-I Chang, “Band expansion-based over-complete independent component analysis for magnetic resonance image analysis,” IEEE Trans. Biomedical Engineering, vol. 55, no. 6, pp. 1666-1677, June 2008.
  2. N. Dobigeon, J. Tourneret and C.-I Chang, “Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery,” IEEE Trans. on Signal Processing, vol. 56, no. 7, pp. 2684-2695, July 2008.
  3. Y. Du and C.-I Chang, “3D combination curves for accuracy and performance analysis of positive biometrics identification,” Optics and Lasers in Engineering, vol. 46, no. 6, pp. 477-490, June 2008.
  4. A. Plaza and C.-I Chang, “Clusters versus FPGAs for real-time processing of hyperspectral imagery,” International Journal of High Performance Computing Applications, vol. 22, no. 4, pp. 366-385, Winter 2008.
  5. M. Hsueh and C.-I Chang, “Field programmable gate arrays for pixel purity index using blocks of skewers for endmember extraction in hyperspectral imagery,” International Journal of High Performance Computing Applications, vol. 22, no. 4, pp. 408-423, Winter 2008.

2007 (5)

  1. J.W. Chai, J. Wang and C.-I Chang, “Mixed PCA/ICA transform for hyperspectral image analysis,” Optical Engineering, vol. 46, no. 7, pp. 077006-1-077006-13, July, 2007.
  2. B.Ramakrishna, C.-I Chang, B. Trout and J. Henqemihle, “Chesapeake bay water quality monitoring using satellite imagery,” International Journal  of High Speed Electronics and Systems (IJHSES), vol. 17, no. 4, pp. 681-688, 2007.
  3. S. Wang and C.-I Chang, “Variable-number variable-band selection for feature characterization in hyperspectral signatures,” IEEE Trans. on Geoscience and Remote Sensing, vol. 45, no. 9, pp. 2979-2992, September 2007.
  4. B. Ramakrishna, W. Liu, K. M. Siddiqui, K.Juluru, N. M. Safdar, C. Chang, E. L. Siegel, “An Automatic tool for assessment of tumor viability and tumor burden in liver tissue on MRI scans,” International Journal of Computer Assisted Radiology and Surgery (CARS), vol. 2, suppl. 1, S519, 2007.

2006 (15)

  1. C.-I Chang and A. Plaza, “Fast iterative algorithm for implementation of pixel purity index,” IEEE Trans. on Geoscience and Remote Sensing Letters, vol. 3, no. 1, pp. 63-67, January 2006.
  2. C.-I Chang and B. Ji, “Weighted least squares error approaches to abundance-constrained linear spectral mixture analysis,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 2, pp. 378-388, February 2006.
  3. C. Kwan, B. Ayhan, G. Chen, J. Wang, B. Ji and C.-I Chang, “A novel approach for spectral unmixing, classification, and concentration estimation of chemical and biological agents,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 2, pp. 409-419, February 2006.
  4. C.-I Chang and M. Hsueh, “Characterization of anomaly detection for hyperspectral imagery,” Sensor Review, vol. 26, no. 2, pp. 137-146, 2006.
  5. C.-I Chang and S. Wang, “Constrained band selection for hyperspectral imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 6, pp. 1575-1585, June, 2006.
  6. J. Wang and C.-I Chang, “Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 6, pp. 1586-1600, June 2006.
  7. A. Plaza, D. Valencia, C.-I Chang and J. Plaza, “Parallel implementation of endmember extraction algorithms from hyperspectral data,” IEEE Trans. on Geoscience and Remote Sensing Letters, vol. 3, no. 7, pp. 334-338,  July 2006.
  8. C.-I Chang and B. Ji, “Fisher’s linear spectral mixture analysis,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 8, pp. 2292-2304, August 2006.
  9. J. Wang and C.-I Chang, “Applications of independent component analysis in endmember extraction and abundance quantification for hyperspectral imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 9, pp. 2601-2616, September 2006.
  10. C.-I Chang, J. Wang, C.-C. Chang and C. Lin, "Progressive coding for hyperspectral signature characterization," Optical Engineering, vol. 45, no. 9, 097002-1-097002-15, September 2006.
  11. C.-I Chang, C. Wu, W. Liu and Y.C. Ouyang, “A growing method for simplex-based endmember extraction algorithms,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 10, pp. 2804-2819, October 2006.
  12. H. Ren, Q. Du, J. Wang, C.-I Chang and J. Jensen, “Automatic target recognition hyperspectral imagery using high order statistics,” IEEE Trans. on Aerospace and Electronic Systems, vol. 42, no. 4, pp. 1372-1385, Oct. 2006.
  13. C.-I Chang, Y. Du, J. Wang, S.-M Guo and P. Thouin, "A survey and comparative study of entropic and relative entropic thresholding techniques," IEE Proceedings, Visong, Image and Signal Processing, vol. 153, no. 6, pp. 837-850, December 2006.
  14. A. Plaza and C.-I Chang, “Impact of initialization on design of endmember extraction algorithms,” IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 11, pp.3397-3407, November, 2006.
  15. P.S. Liao, S.M. Guo, N-S. Yu, C.-Y. Chen, S.K. Lee and C.-I Chang, “Mass detection in mammography using principle component analysis and stepwise selection,” Chinese J. Radiology, vo. 31, pp. 275-287, 2006.

2005 (3)

  1. C.-I Chang, “Orthogonal subspace projection revisited: a comprehensive study and analysis,” IEEE Trans. on Geoscience and Remote Sensing, vol. 43, no. 3, pp. 502-518, March 2005.
  2. S.-C. Yang, G.-C. Hsu, P. C. Chung, C. M. Wang, S.M. Guo, C.-S. Lo, C.-W. Yang, S.-K. Lee, C.-I Chang, “3-D localization of clustered microcalcifications using cranio-caudal and medio-lateral oblique views,” Computerized Medical Imaging and Graphics, vol. 29, pp. 521-532, 2005.
  3. S.C. Yang, C.M. Wang, Y.N. Chung, G.C. Hsu, S.K. Lee, P.C. Chung, C.I. Chang, “A Computer-Aided System for Mass Detection and Classification in Digitized Mammograms,” Biomedical Engineering Applications Basis and Communications, vol. 17, no. 5, pp. 215-228 , Oct. 2005.

2004 (7)

  1. Y. Du, C.-I Chang, C.-C. Chang, F. D’Amico and J.O. Jensen, "A new hyperspectral measure for material discrimination and identification," Optical Engineering, vol. 43, no. 8, pp. 1777-1786, August 2004.
  2. C.-I Chang and Y. Chen, “Gradient texture unit coding for texture analysis,” Optical Engineering, vol. 43, no. 8, pp. 1891-1903, August 2004.
  3. C.-I Chang, H. Ren, C.-C. Chang, J.O. Jensen and F. D’Amico, "Estimation of subpixel target size for remotely sensed imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 42, no. 6, pp. 1309-1320, June 2004.
  4. Y. Du, C.-I Chang and P. Thouin, “Unsupervised thresholding of video images,” Optical Engineering, vol. 43, no. 2, pp. 282-289, February 2004.
  5. C.-I Chang and Q. Du, "Estimation of number of spectrally distinct signal sources in hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 42, no. 3, pp. 608-619, March 2004.
  6. Q. Du and C.-I Chang, "Linear mixture analysis-based compression for hyperspectral image analysis," IEEE Trans. on Geoscience and Remote Sensing,  vol. 42, no. 4, pp. 875-891, April 2004.
  7. Q. Du and C.-I Chang, "A signal-decomposed and interference-annihilated approach to hyperspectral target detection," IEEE Trans. on Geoscience and Remote Sensing vol. 42, no. 4, pp. 892-906, April 2004.

2003 (6)

  1. C.M. Wang, C.C. Chen, Y.-N. Chung, S.-C. Yang, P.C. Chung, C.W. Yang and C.-I Chang, "Detection of spectral signatures in MR images for classification," IEEE Trans. on Medical Imaging, vol. TMI-22, no. 1, pp. 50-61, Jan. 2003.
  2. S.K. Lee, P.-C. Chung, C.-I Chang, C.-S. Lo, T. Lee, G.-C. Hsu and C.-W. Yang, “Classification of clustered microcalcifications using a shape cognitron,” Neural Networks, vol. 16, pp. 121-132, 2003.
  3. Y. Du, C.-I Chang and P. Thouin, “An automatic system for text detection in single video images,” J. Electronic Imaging, vol. 12, no. 3, pp. 410-422, July 2003.
  4. Q. Du, H. Ren and C.-I Chang, “A comparative study for orthogonal subspace projection and constrained energy minimization” IEEE Trans. on Geoscience and Remote Sensing, vol. 41, no. 6, pp. 1525-1529, June 2003.
  5. S.M. Guo, P.S. Liao, Y.C. Liao, S.C. Yang, P.C. Chung and C.-I Chang, “Mass detection in mammography using texture analysis,” Chinese Journal of Radiology, vol. 28, no. 3, pp. 149-157, June 2003.
  6. H. Ren and C.-I Chang, "Automatic spectral target recognition in hyperspectral imagery," IEEE Trans. on Aerospace and Electronic Systems, vol. 39, no. 4, pp. 1232-1249, October 2003.

2002 (5)

  1. C.-I Chang, S.S. Chiang, J.A. Smith and I.W. Ginsberg, "Linear spectral random mixture analysis for hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 40, no. 2, pp. 375-392, February 2002.
  2. C.-I Chang, "Target signature-constrained mixed pixel classification for hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 40, no. 5, pp. 1065-1081, May 2002.
  3. S.-C. Yang, S.-K. Lee, P.C. Chung, C.W. Yang, T. Lee,  G.-C. Hsu, C.-W. Yang C.-I Chang and C.-S. Luo, "A computer-aided diagnostic system for detection and segmentation of clustered microcalcifications in digital mammograms," Chinese Journal of Radiology, vol. 27, no. 3, pp. 89-101, June 2002. (in Chinese)
  4. C.M. Wang, C.C. Chen, S.-C. Yang, Y.-N. Chung, P.C. Chung, C.W. Yang and C.-I Chang, "An unsupervised Orthogonal subspace projection approach to MR image classification MR images for classification," Optical Engineering, vol. 41, no. 7, pp. 1546-1557, July 2002.
  5. C.-I Chang and S.-S. Chiang, "Anomaly detection and classification for hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 40, no. 6, pp. 1314-1325, June 2002.

2001 (9)

  1. Q. Du and C.-I Chang, "A linear constrained distance-based discriminant analysis for hyperspectral image classification," Pattern Recognition, vol. 34, no. 2, pp. 361-373, February 2001.
  2. D. Heinz and C.-I Chang, "Fully constrained least squares linear mixture analysis for material quantification in hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 39, no. 3, pp. 529-545, March 2001.
  3. C.-I Chang, H. Ren and S.S. Chiang, "Real-time processing algorithms for target detection and classification in hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 39, no. 4, pp. 760-768, April  2001.
  4. P. Thouin and C.-I Chang, "A computer-automated system for restoration of documents and text images," Journal of Electronic Imaging, vol. 10, no. 2, pp. 535-547, April 2001.
  5. S.S. Chiang, C.-I Chang and I.W. Ginsberg, "Unsupervised subpixel target detection for hyperspectral images using projection pursuit," IEEE Trans. on Geoscience and Remote Sensing,  vol. 39, no. 7, pp. 1380-1391, July 2001.
  6. Q. Du and C.-I Chang, "A hidden Markov model approach to spectral analysis for hyperspectral imagery," Optical Engineering, vol. 40, no. 10, pp. 2277-2284, October 2001.
  7. K. Guilfoyle, M.L.G. Althouse and C.-I Chang, "A quantitative and comparative analysis of linear and nonlinear spectral mixture models using radial basis function neural networks," IEEE Trans. on Geoscience and Remote Sensing,  vol. 39, no. 10, pp. 2314-2318, October 2001.
  8. C.-M. Wang, S-C. Yang, P.-C. Chung, C.S. Lo, C.-I Chang, C.C. Chen, C.-W. Yang and C.H. Wen, "Orthogonal subspace projection-based approaches to classification of MR image sequences," Computerized Medical Imaging and Graphics, vol. 25, no. 6, pp. 465-476, October 2001.
  9. S.-K. Lee, S.-C. Yang, P.C. Chung, C.-S. Lo, C.-W. Yang and C.-I Chang, "Three dimensional localization of microcalcification on X-ray mammograms," Chinese Journal of Radiology, vol. 26, no. 3, pp. 107-118, 2001. (in Chinese)

2000 (12)

  1. C.-I Chang and H. Ren, "An experiment-based quantitative and comparative analysis of hyperspectral target detection and image classification algorithms," IEEE Trans on Geoscience and Remote Sensing, vol. 38, no. 2, pp. 1044-1063, March 2000.
  2. C.-I Chang and D. Heinz, "Constrained subpixel detection for remotely sensed images," IEEE Trans. on Geoscience and Remote Sensing, vol. 38, no. 3, pp. 1144-1159, May 2000.
  3. C.-I Chang, J.-M. Liu, B.-C. Chieu, C.-M. Wang, C. S. Lo, P.-C. Chung, H. Ren, C.-W. Yang, D.-J. Ma, "A generalized constrained energy minimization approach to subpixel target detection for multispectral imagery," Optical Engineering, vol. 39, no. 5, pp. 1275-1281, May 2000.
  4. C.-W. Yang, D.-J. Ma, S.-C. Chao, C.-M. Wang, C.H. Wen, S.C. Lo, P.-C. Chung and C.-I Chang, "A computer-aided diagnostic detection system of venous beading in retinal images," Optical Engineering, vol. 39, no. 5, pp. 1293-1303, May 2000.
  5. P. Thouin and C.-I Chang, "A method for restoration of low-resolution text images," International Journal on Document Analysis and Recognition, Vol. 2, No. 4, pp. 200-210, June 2000.
  6. J. Zhang, C.-I Chang, S.J. Miller, K.A. Kang, "A feasibility study on multi-spectral image analysis of skin tumors," Biomedical Instrumentation and Technology, vol. 34, no. 4, pp. 275-282, July/August 2000.
  7. C.-I Chang, "An information theoretic-based approach to spectral variability, similarity and discriminability for hyperspectral image analysis," IEEE Trans. on Information Theory, vol. 46, no. 5, pp. 1927-1932, August 2000.
  8. S.-K. Lee, C.-S. Lo, C.-M. Wang, P.-C. Chung, C.-I Chang, C.-W. Yang and P.-C. Hsu, "A computer-aided design mammography screening system for detection and classification of microcalcifications," J. Medical Informatics, vol. 60, no. 1, pp. 29-57, Oct. 2000.
  9. H. Ren and C.-I Chang, "A generalized orthogonal subspace projection approach to unsupervised multispectral image classification," IEEE Trans. on Geoscience and Remote Sensing, vol. 38, no. 6, pp. 2515-2528, November 2000.
  10. A. Ifarraguerri and C.-I Chang, "Unsupervised hyperspectral image analysis with projection pursuit," IEEE Trans. on Geoscience and Remote Sensing, vol. 38, no. 6, pp. 2529-2538, November 2000.
  11. H. Ren and C.-I Chang, "Target-constrained interference-minimized approach to subpixel target detection for hyperspectral imagery," Optical Engineering, vol. 39, no. 12, pp. 3138-3145, December 2000.
  12. C.-S. Lo, P.-C. Chung, S.-K. Lee, C.-I Chang, T. Lee, G.C. Hsu and C.W. Yang, "Off-line mammography screening system embedded with hierarchically-coarse-to-fine techniques for the detection and segmentation of clustered Microcalcifications," Institute of Electronics, Information, Communication Engineers (IEICE) Transaction on Information and System, vol. E83-D, pp. 2161-2173, no. 12, December 2000.

1999 (8)

  1. C.-I Chang and C. Brumbley, "A Kalman filtering approach to multispectral image classification and detection of changes in signature abundance," IEEE Trans. on Geoscience and Remote Sensing, vol. 37, no. 1,  pp. 257-268, January 1999.
  2. C.-I Chang and C. Brumbley, "Kalman filtering approach to multispectral/hyperspectral image classification," IEEE Trans. Aerospace and Electronics Systems, vol. 37, no 1, pp. 319-330, January 1999.
  3. A. Ifarraguerri and C.-I Chang, "Hyperspectral image segmentation with convex cones," IEEE Trans. on Geoscience and Remote Sensing, vol. 37, no 2, pp. 756-770, March 1999.
  4. C. Brumbley and C.-I Chang, "An unsupervised vector quantization-based target signature subspace projection approach to classification and detection in unknown background," Pattern Recognition, vol. 32, no. 7, pp. 1161-1174, July 1999.
  5. T.M. Tu, H.C. Shy, C.-H. Lee and C.-I Chang, "An oblique subspace projection to mixed pixel classification in hyperspectral images," Pattern Recognition, vol. 32, no. 8, pp. 1399-1408, August, 1999.
  6. C.-I Chang and Q. Du, "Interference and noise adjusted principal components analysis," IEEE Trans. on Geoscience and Remote Sensing, vol. 37, no. 5, pp. 2387-2396, September 1999.
  7. C.-I Chang, Q. Du, T.S. Sun and M.L.G. Althouse, "A joint band prioritization and band decorrelation approach to band selection for hyperspectral image classification," IEEE Trans. on Geoscience and Remote Sensing, vol. 37, no. 6, pp. 2631-2641, November 1999.
  8. J.-R. Tsai. P.C. Chung and C.-I Chang, "Robust radial basis function neural networks,"  IEEE Trans. System, Man, Cybernetics-Part B: Cybernetics, vol. 29, no. 6, pp. 674-685, December 1999.

1998 (7)

  1. T.M. Tu, C.-H. Chen and  C.-I Chang, "A noise  subspace projection approach to target signature detection and extraction in unknown background for hyperspectral images," IEEE Trans. on Geoscience and Remote Sensing, vol. 36, no. 1, pp. 171-181,  January 1998.
  2. T.M. Tu, C.-H. Chen, J-L. Wu and  C.-I Chang, "A fast two-stage classification method for high dimensional remote sensing data," IEEE Trans. on Geoscience and Remote Sensing, vol. 36, no. 1, pp. 182-191,  January 1998.
  3. C.-I Chang, T.-L.E. Sun and M.L.G. Althouse, "An unsupervised interference rejection approach to target detection and classification for hyperspectral imagery," Optical Engineering, vol. 37, no. 3, pp. 735-743, March 1998.
  4. C.-I Chang, "Further results on relationship between spectral unmixing and subspace projection," IEEE Trans. on Geoscience and Remote Sensing, vol. 36, no. 3, pp. 1030-1032,  May 1998.
  5. C.-I Chang, X. Zhao, M.L.G. Althouse and J.-J. Pan, "Least squares subspace projection approach to mixed pixel classification in hyperspectral images," IEEE Trans on Geoscience and Remote Sensing, vol. 36, no. 3, pp. 898-912, May 1998.
  6. E-L. Chen, P.-C. Chung, C.-L Chen, H.-M. Tsai and C.-I Chang, "An automatic diagnostic system for CT liver image classification," IEEE Trans. Biomedical Engineering, vol. 45, no. 6, pp. 783-794, June 1998.
  7. P. Thouin and C.-I Chang, "New technique restores text from 8x8 block DCT-compressed gray-scale images," Special Section on J. Electronic Imaging, OE Report, no. 179, p. 11, November 1998.

1997 (3)

  1. T.M. Tu, C.-H. Chen and  C.-I Chang, "A posteriori least squares orthogonal subspace projection approach to weak signature extraction and detection," IEEE Trans. on Geoscience and Remote Sensing, vol. 35, no. 1, pp. 127-139,  January 1997.
  2. C.-W. Yang, P.-C. Chung and C.-I Chang, "An image capture and communication system for emergency computed tomography," Computer Methods and Programs in Biomedicine, vol. 52, pp. 139-145, 1997.
  3. C.-W. Yang, P.-C. Chung, C.-I Chang, S.-K. Lee and L.-Y. Kung, "A hierarchical model for PACS," Computerized Methods in Medical Images and Graphics, vol. 21, no. 1, pp. 29-37, 1997.

1996 (1)

  1. C.-W. Yang, P.-C. Chung and C.-I Chang, "A hierarchical fast two-dimensional entropic thresholding algorithm using a histogram pyramid," Optical Engineering, vol. 35, no. 11, pp. 3227-3241, November 1996.

1995 (1)

  1. M.L.G. Althouse and C.-I Chang, "Target detection in multispectral imagery using spectral co-occurrence matrix and entropy thresholding," Optical Engineering, vol. 34, pp. 2135-2148, July 1995.

1994 (2)

  1. J.C. Harsanyi and C.-I Chang, "Hyperspectral image classification and dimensionality  reduction: an orthogonal subspace projection approach," IEEE Trans. on Geoscience and Remote Sensing, vol. 32, no. 4, pp. 779-785, July, 1994.
  2. C.-I Chang, K. Chen, J. Wang and M.L.G. Althouse, "A relative entropy approach to image thresholding,"  Pattern  Recognition, vol. 27, no. 9, pp. 1275-1289, Sep. 1994.

1993 (2)

  1.  L.B. Wolfe and C.-I Chang, "A complete sufficient statistic for finite-state Markov processes with applications to source coding," IEEE Trans. on Inform. Theory, vol. 39, no. 3, pp. 1047-1049, May 1993.
  2. L.B. Wolfe and C.-I Chang, "A simple method for calculating the rate distortion function of a source with an unknown parameter," Signal Processing, vol. 33, pp. 209-221, 1993.

1992 (2)

  1. C.-I Chang and L.B. Wolfe, "Source matching problems revisited," IEEE Trans. on Inform. Theory, vol. 38, no. 4, pp. 1391-1395, July 1992. 
  2. J.J. Pan and C.-I Chang, "Destriping of LANDSAT MSS Images by Filtering Techniques," Photogrammetric Engineering and Remote Sensing, vol. 58, no. 10, pp. 1417-1723, October 1992.

1991 (1)

  1. M.L.G. Althouse and C.-I Chang, "Chemical vapor detection with a multispectral thermal imager," Optical Engineering, vol. 30, no. 11, pp. 1725-1733, July 1991. (invited paper)

1990 (3)

  1. C.-I Chang, "A minimax approach to calculating the capacity of discrete channels," Soochow Journal of Mathematics, vol. 16, no. 2, pp. 221-230, Sep. 1990.
  2. C.-I Chang, S.C. Fan and L.D. Davisson, "On numerical methods of calculating the capacity of a continuous-input discrete-output memoryless channel," Information and Computation, vol. 86, no. 1,  pp. 1-13, May 1990. 
  3. C.-I Chang and L.D. Davisson, "Two iterative algorithms for finding minimax solutions," IEEE Trans. on Inform. Theory, vol. IT-36, no. 1, pp. 126-140, Jan. 1990.

1988 (1)

  1. C.-I Chang and L.D. Davisson, "On calculating the capacity of an infinite-input finite (infinite)-output channel," IEEE Trans. on Inform. Theory, Vol. IT-34, No. 5, pp. 1004-1010, Sep. 1988.

1985 (1)

  1. H.V. Poor and C.-I Chang, "A reduced complexity quadratic structure for the detection of stochastic signals," J. Acoust. Soc. Am., Vol. 78, no. 5, pp. 1652-1657, Nov. 1985.

PAPERS SUBMITTED TO REFEREED JOURNAL PUBLICATION (9)

  1. C.-I Chang, W. Xiong, “Convex cone volume analysis for endmember extraction in hyperspectral imagery,” IEEE Trans. on Geoscience and Remote Sensing.
  2. C.-I Chang, W. xiong and X. Jiao, “High order statistics-based for VD estimation,” IEEE Trans. on Geoscience and Remote Sensing.
  3. C.-I Chang, E. Wong, H.M. Chen, S.Y. Chen, J.W. Chai, C.C.C. Chen, C.W. Yang, S. K. Lee, Y.C. Ouynag and Y.K. Wong, “Intra-pixel multispectral processing of brain magnetic resonance images for tissue charactetization,” Current Medical Imaging Review.
  4. C.C.C. Chen, J.-W. Chai, H.M. Chen, S.Y. Chen, Y.C. Ouyang, C.W. Yang, S. K. Lee and C.-I Chang, “Unsupervised classification for magnetic resonance images,” IEEE Trans. on Medical Imaging.
  5. C.C.C. Chen, H.M. Chen, S.Y. Chen, B.H. Lin, Y.C. Ouyang, C.W. Yang, S. K. Lee and C.-I Chang, “Weighted kernel-based support vector machine apporach to magnetic resonance images,” Computerized Medical Imaging and Graphics.
  6. Y-J Chiou, C.C.C. Chen, H.M. Chen, S.Y. Chen, C.W. Yang, S. K. Lee, Y.C. Ouyang, W.C. Su and C.-I Chang, “Volume sphering analysis for magnetic resonance image classification,” Computerized Medical Imaging and Graphics..
  7. H.M. Chen, S.Y. Chen, J.W. Chai, C.C.C. Chen, C.W. Yang, S. K. Lee, Y.C. Ouyang and C.-I Chang, “Hierarchical multi-class support vector machines,” Pattern Recognition.
  8. H.M. Chen, S.Y. Chen, J.W. Chai, C.C.C. Chen, C.W. Yang, S. K. Lee, Y.C. Ouyang and C.-I Chang, “Iterative Fisher’s linear discriminant analysis,” Pattern Recognition.
  9. C.-I Chang and K.-H. Liu, “Dynamic band selection for hyperspectral imagery,” IEEE Trans. on Geoscience and Remote Sensing.
  10. C. Lin, S.Y. Chen, H.M. Chen, C.C. Wu, Y.C. Ouyang and C.-I Chang, “A pixel purity index approach to unsupervised multispectral image classification,” IEEE Trans. on Geoscience and Remote Sensing Letters.
  11. S. Chakravarty and C.-I Chang, “Block truncation signature coding,” J. Electronic Imaging.

BOOK CHAPTERS (17)

2011 (1)

  1. H. Safavi, based dimensionality reduction for hyperspectral analysis,” Chapter 13, Recent Advances in Satellite Data Compression, edited by B. Huang, Springer-Verlag, 2011.

2007 (5)

  1. C.-I Chang, Overview, Chapter 1: Overview, Hyperspectral Data Exploitation: Theory and Applications, edited by C.-I Chang, pp. 1-16, John Wiley & Sons, 2007.
  2. C.-I Chang, Chapter 3: Information-Processed Matched Filters for Hyperspectral Target Detection and Classification, Hyperspectral Data Exploitation: Theory and Applications, edited by C.-I Chang, pp. 47-74, John Wiley & Sons, 2007.
  3. A. Plaza and C.-I Chang, Chapter 1: Introduction, High-Performance Computing in Remote Sensing, edited by A. Plaza and C.-I Chang, pp. 1-7, CRC Press, 2007.
  4. A. Plaza and C.-I Chang,, Chapter 2: High Performance Computer Architectures for Remote Sensing Data Analysis: Overview and Case Study, High-Performance Computing in Remote Sensing, edited by A. Plaza and C.-I Chang, pp. 9-41, CRC Press, 2007.
  5. J. Wang and C.-I Chang, Chapter 16: FPGA Design for Real-time Implementation of Hyperspectral Target Detection and Classification Algorithms, High-Performance Computing in Remote Sensing, edited by A. Plaza and C.-I Chang, pp. 379-395, CRC Press, 2007.

2006 (7)

  1. B. Ramakishna, A. Plaza, C.-I Chang, H. Ren, Q. Du and C.-C. Chang, Spectral/Spatial Hyperspectral Image Compression, Hyperspectral Data Compression, edited by G. Motta, F. Rizzo  and J. Storer, pp. 309-347, Springer-Verlag, 2006.
  2. C.-I Chang, Chapter 1: Utility of Virtual Dimensionality in Hyperspectral Signal/Image Processing, Recent Advances in Hyperspectral Signal and Image Processing, edited by C.-I Chang, Trivandrum, Kerala: Research Signpost, India, 2006, pp. 1-27.
  3. F. Chaudhry, C. Wu, W. Liu, C.-I Chang and A. Plaza, Chapter 2: Pixel Purity Index-Based Algorithms for Endemember Extraction from Hyperspectral Imagery, Recent Advances in Hyperspectral Signal and Image Processing, edited by C.-I Chang,  Trivandrum, Kerala: Research Signpost, India, 2006, pp. 29-61.
  4. B. Ji and C.-I Chang, Chapter 3: Principal Components Analysis-based Endmember Extraction Algorithms, Recent Advances in Hyperspectral Signal and Image Processing, edited by C.-I Chang, Trivandrum, Kerala: Research Signpost, India, 2006, pp. 63-91.
  5. W. Liu, X. Jiao, B. Ji, S. Yang and C.-I Chang, Chapter 4: A Study on Purdue’s Indian Pine Test Site, Chapter 4,  Recent Advances in Hyperspectral Signal and Image Processing, edited by C.-I Chang, Trivandrum, Kerala: Research Signpost, India, 2006, pp. 93-139.
  6. J. Wang and C.-I Chang, Chapter 5: A Low Probability Detector-Based Unsupervised Background Suppression, Target Detection and Classification for Hyperspectral Imagery, Chapter 5, Recent Advances in Hyperspectral Signal and Image Processing, edited by C.-I Chang, Trivandrum, Kerala: Research Signpost, India, 2006, pp. 141-169.
  7. S. Wang and C.-I Chang, Chapter 6: Kalman Filter-Based Approaches to Hyperspectral Signal Similarity and Discrimination, Recent Advances in Hyperspectral Signal and Image Processing, edited by C.-I Chang, Trivandrum, Kerala: Research Signpost, India, 2006, pp. 171-194.

2005 (2)

  1. Y.W. Chang, Y.C. Chang, C.-I Chang, G.-C. Hsu, H.-H. Hsu, S.-M. Guo, S.-C. Yang, P-C. Chung, S.-K. Lee, Chapter 3: Computer-Aided Diagnosis for Breast Cancer Detection by Mammography, Chapter 3, Recent Research Developments in Biomedical Engineering, ed. S.G. Pandalai, vol. 2, Trivandrum, Kerala: Research Signpost, India, pp. 53-92, 2005.
  2. C.C. Chen, C.-M. Wang, C.-I Chang, C.-W. Yang, J. W. Chai, Y.-N. Chung, P.-C. Chung, Chapter 9: Techniques in Detection of Spectral Signatures in MR Images and Their Applications, Medical Imaging Systems: Technology & Applications, edited by C.T. Leondes, Vol. 4, pp. 297-327, World Scientific Publishing, 2005.

2000 (1)

  1. C.-I Chang, M. Cao and H. Ko, Image Compression Using Karhunen Loeve Transform Quantization-Based Neural Network, Encyclopedia of Microcomputers, vol. 24, Supplement 3, ed. by A. Kent and J.G. Williams, pp. 175-191, Marcel Dekker, Inc., 2000.

1999 (1)

  1. C.-I Chang, Least Squares Error Theory for Linear Mixing Problems with Mixed Pixel Classification for Hyperspectral Imagery, Recent Research Developments in Optical Engineering, ed. S.G. Pandalai, vol. 2, 1999, pp. 241-268, Trivandrum, Kerala: Research Signpost, India.