The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.04 - April (2008 vol.20)
pp: 562-575
ABSTRACT
This paper adresses the problem of building an index of compressed object data-base. We introduce an informational similarity measure based on coding length of two part codes. Then, we present a methodology to compress the data-base by taking into account inter-object redundancies and by using the informational similarity measure. The method produces an index included in the code of the data-volume. This index is built such that it contains the minimal sufficient information to discriminate the data-volume objects. Then, we present an optimal two part coder for compressing spatio-temporal events contained in Satellite Image Time Series (SITS). The two part coder allows us to measure similarity and, then, to derive an optimal index of SITS spatio-temporal events. The resulting index is representative of the SITS information content and enables queries based on information content.
INDEX TERMS
IIndex Generation, Model classification, Remote sensing, Clustering, Pattern Recognition, Statistical, Time-varying imagery, Models, Compression (Coding), Model-based coding, Texture, Content Analysis and Indexing, Information Search and Retrieval, Information theory
CITATION
Lionel Gueguen, Mihai Datcu, "A Similarity Metric for Retrieval of Compressed Objects: Application for Mining Satellite Image Time Series", IEEE Transactions on Knowledge & Data Engineering, vol.20, no. 4, pp. 562-575, April 2008, doi:10.1109/TKDE.2007.190718
REFERENCES
[1] A.W.M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, “Content-Based Image Retrieval at the End of the Early Years,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 12, pp. 1349-1380, Dec. 2000.
[2] S. Antani, R. Kasturi, and R. Jain, “A Survey on the Use of Pattern Recognition Methods for Abstraction, Indexing and Retrieval of Images and Video,” Pattern Recognition, vol. 35, pp. 945-965, 2002.
[3] M. Datcu and K. Seidel, “Image Information Mining: Exploration of Image Content in Large Archives,” Proc. IEEE Aerospace Conf. '00, vol. 3, pp. 253-264, Mar. 2000.
[4] M. Datcu, K. Seidel, S. D'Elia, and P.G. Marchetti, “Knowledge-Driven Information Mining in Remote-Sensing Image Archives,” ESA Bull., vol. 110, pp. 26-33, May 2002.
[5] T. Minka and R. Picard, “Interactive Learning Using a Society of Models,” Pattern Recognition, vol. 4, no. 30, pp. 565-581, 1997.
[6] M. Datcu et al., “Information Mining in Remote Sensing Image Archives: System Description,” IEEE Trans. Geoscience and Remote Sensing, vol. 41, no. 12, pp. 2923-2936, Dec. 2003.
[7] R.M. Gray and D.L. Neuhoff, “Quantization,” IEEE Trans. Information Theory, vol. 44, no. 6, pp. 2325-2383, Oct. 1998.
[8] P. Mitra, C.A. Murthy, and S.K. Pal, “Unsupervised Feature Selection Using Feature Similarity,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 3, pp. 301-312, Mar. 2002.
[9] C. Podilchuk and X. Zhang, “Face Recognition Using DCT-Based Feature Vectors,” Proc. 21st IEEE Int'l Conf. Acoustics, Speech, and Signal Processing (ICASSP '96), vol. 4, pp. 2144-2147, May 1996.
[10] F. Idris and S. Panchanathan, “Image Indexing Using Wavelet Vector Quantization,” Proc. SPIE Digital Image Storage Archiving Systems, vol. 2606, pp. 269-275, Oct. 1995.
[11] H. Wang, A. Divakaran, A. Vetro, S.-F. Chang, and H. Sun, “Survey of Compressed-Domain Features Used in Audio-Visual Indexing and Analysis,” J. Visual Comm. and Image Representation, vol. 14, pp. 150-183, 2003.
[12] J.J. Rissanen, “A Universal Data Compression System,” IEEE Trans. Information Theory, vol. 29, no. 5, pp. 656-664, Sept. 1983.
[13] A.N. Kolmogorov, “Three Approaches to the Quantitative Definition of Information,” Problems of Information Transmission, vol. 1, no. 1, pp. 1-7, 1965.
[14] M. Weinberger, G. Seroussi, and G. Sapiro, “LOCO-I: A Low Complexity, Content-Based, Lossless Image Compression Algorithm,” Proc. Sixth IEEE Data Compression Conf. (DCC '96), pp. 140-149, Mar. 1996.
[15] M.J. Weinberger, J.J. Rissanen, and R.B. Arps, “Applications of Universal Context Modeling to Lossless Compression of Gray-Scale Images,” IEEE Trans. Image Processing, vol. 5, no. 4, pp. 575-586, Apr. 1996.
[16] L. Gueguen, M. Trocan, B. Pesquet-Popescu, A. Giros, and M. Datcu, “A Comparison of Multispectral Satellite Sequence Compression Approaches,” Proc. IEEE Int'l Symp. Signals, Circuits and Systems (ISSCS '05), vol. 1, pp. 87-90, July 2005.
[17] C.E. Shannon, “A Mathematical Theory of Communication,” The Bell System Technical J., vol. 27, pp. 379-423, July-Oct. 1948.
[18] P. Grünwald and P. Vitanyi, “Shannon Information and Kolmogorov Complexity,” IEEE Trans. Information Theory, Sept. 2004.
[19] J.J. Rissanen, “Universal Coding, Information, Prediction and Estimation,” IEEE Trans. Information Theory, vol. 30, no. 4, pp. 629-636, July 1984.
[20] M. Li, X. Chen, X. Li, B. Ma, and P.M.B. Vitanyi, “The Similarity Metric,” IEEE Trans. Information Theory, vol. 50, no. 12, pp. 3250-3264, Dec. 2004.
[21] S.C. Johnson, “Hierarchical Clustering Schemes,” Psychometrika, vol. 32, no. 3, pp. 241-254, Sept. 1967.
[22] A.C. Popat, “Conjoint Probabilistic Subband Modeling,” PhD dissertation, Massachusetts Inst. of Tech nology, Sept. 1997.
[23] M. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I Lossless Image Compression Algorithm: Principles and Standardization into JPEG-LS,” IEEE Trans. Image Processing, vol. 9, no. 8, pp. 1309-1324, Aug. 2000.
[24] M. Schroder, H. Rehrauer, K. Seidel, and M. Datcu, “Spatial Information Retrieval from Remote-Sensing Images—Part 2: Gibbs-Markov Random Fields,” IEEE Trans. Geoscience and Remote Sensing, vol. 36, no. 5, pp. 1446-1455, Sept. 1998.
[25] G.R. Cross and A.K. Jain, “Markov Random Field Texture Models,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 5, no. 1, pp. 25-39, Jan. 1983.
[26] S.R. Lele and J.K. Ord, “Conditional Least Squares Estimation for Spatial Processes: Some Asymptotic Results,” Technical Report 65, Dept. of Statistics, Pennsylvania State Univ., 1986.
[27] F. Spitzer, “Markov Random Fields and Gibbs Ensembles,” The Am. Math. Monthly, vol. 78, no. 2, pp. 142-154, Feb. 1971.
[28] X. Wu and N. Memon, “Context-Based, Adaptive, Lossless Image Coding,” IEEE Trans. Comm., vol. 45, no. 4, pp. 437-444, Apr. 1997.
7 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool