A new image representation algorithm inspired by image submodality models, redundancy reduction, and learning in biological vision

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 27, Issue 9, 2005, Pages 1367-1378

  Balakrishnan, Nikhil ^a   Hariharakrishnan, Karthik ^b   Schonfeld, Dan ^c  

^a University of Illinois at Chicago   (United States)

^b Motorola India Pvt Ltd   (India)

^c 1120 Science and Engineering Offices   (United States)

Author keywords

Clustering algorithms; Color; Computer vision; Feature representation; Machine learning; Statistical models

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COLOR; COMPUTER VISION; FEATURE EXTRACTION; IMAGE QUALITY; INDEPENDENT COMPONENT ANALYSIS; LEARNING SYSTEMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PRINCIPAL COMPONENT ANALYSIS;

CLUSTERING ALGORITHMS; FEATURE REPRESENTATION; STATISTICAL MODELS;

IMAGE CODING;

ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BIOMIMETICS; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; PHYSIOLOGY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; VISION;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; BIOMIMETICS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; VISUAL PERCEPTION;

EID: 25844493055     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2005.170     Document Type: Article

References (25)

1. B.A. Olshausen and D.J. Field, "Sparse Coding with an Over-complete Basis Set: A Strategy Employed by V1?" Vision Research, vol. 37, no. 23, pp. 3311-3325, 1997.
2. R.S. Snell, Clinical Neuroanatomy for Medical Students, pp. 702-720. Philadelphia: Lippincott Williams and Wilkins, 1997.
3. Neural Codes and Distributed Representations: Foundations of Neural Computation, L. Abbott and T.J. Sejnowski, eds. Cambridge, Mass.: MIT Press, 1999.
4. J. Daugman, "Gabor Wavelets and Statistical Pattern Recognition," The Handbook of Brain Theory and Neural Networks, second ed., M.A. Arbib, ed., pp. 457-463. Cambridge: MIT Press, 2003.
5. H. Neumann and E. Mingolla, "Contour and Surface Perception," The Handbook of Brain Theory and Neural Networks, second ed., M.A. Arbib, ed., pp. 271-276. Cambridge: MIT Press, 2003.
6. H.B. Barlow, "Possible Principles Underlying the Transformations of Sensory Messages," Sensory Comm., W.A. Rosenblith, ed., pp. 217-234. Cambridge: MIT Press, 1961.
7. H.B. Barlow, "Unsupervised Learning," Neural Computation, vol. 1, pp. 295-311, 1989.
8. H.B. Barlow, "Redundancy Reduction Revisited," Network: Computation in Neural Systems, vol. 12, pp. 241-253, 2001.
9. J.A. McArthur and B. Moulden, "A Two-Dimensional Model of Brightness Perception Based on Spatial Filtering Consistent with Retinal Processing," Vision Research, vol. 39, pp. 1199-1219, 1999.
10. E.H. Land and J.J. McCann, "Lightness and Retinex Theory," J. Optical Soc. Am., vol. 61, pp. 1-11, 1971.
11. A. Hurlbert, "Formal Connections between Lightness Algorithms," J. Optical Soc. Am., vol. 3, pp. 1684-1693, 1986.
12. S. Grossberg and D. Todorovié, "Neural Dynamics of 1-D and 2-D Brightness Perception: A Unified Model of Classical and Recent Phenomena," Perception & Psychophysics, vol. 43, pp. 723-742, 1988.
13. M.A. Paradiso and K. Nakayama, "Brightness Perception and Filling-In," Vision Research, vol. 39, pp. 1221-1236, 1991.
14. R. Kentridge, C. Heywood, and J. Davidoff, "Color Perception," The Handbook of Brain Theory and Neural Networks, second ed., M.A. Arbib, ed., pp. 230-233. Cambridge Mass.: MIT Press, 2003.
15. A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. New York: John Wiley & Sons, 2001.
16. A. Hyvärinen, "Fast ICA Matlab Package," http://www.cis. hut.fi/projects/ica/fastlab, Apr. 2003.
17. A. Hyvärinen and P. Hoyer, "Emergence of Phase and Shift Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces," Neural Computation, vol. 12, no. 7, pp, 1705-1720, 2000.
18. A. Hyvärinen, P.O. Hoyer, and M. Hinki, "Topographic Independent Component Analysis," Neural Computation, vol. 13, no. 7, pp. 1527-1558, 2001.
19. M. Tipping and C. Bishop, "Mixtures of Probabilistic Principal Component Analyzers," Neural Computation, vol. 11, no. 2, pp. 443-482, 1999.
20. I. Nabney and C. Bishop, "Netlab Neural Network Software," http://www.ncrg.aston.ac.uk/netlab, July 2003.
21. R.C. Gonzalez and R.E. Woods, Digital Image Processing. Reading, Mass.: Addison Wesley, 1993.
22. T.M. Cover and J.A. Thomas, Elements of Information Theory, pp. 12-49. New York: John Wiley & Sons, 1991.
23. D.H. Ballard, An Introduction to Natural Computation, pp. 46-48. Cambridge, Mass,: MIT Press, 1999.
24. N. Krüger, "Collinearity and Parallelism are Statistically Significant Second Order Relations of Complex Cell Responses," Neural Processing Letters, vol. 8, pp. 117-129, 1998.
25. W.S. Geisler, J.S. Perry, B.J. Super, and D.P. Gallogly, "Edge Co-Occurrence in Natural Images Predicts Contour Grouping Performance," Vision Research, vol. 41, pp. 711-724, 2001.