Multiridgelets for texture analysis

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7248, Issue , 2009, Pages

  Yoon, Hong Jun ^a   Li, Ching Chung ^a  

^a University of Pittsburgh   (United States)

Author keywords

Multiridgelets; Multiwavelets; Ridgelets; Texture analysis

Indexed keywords

2D WAVELETS; BALANCED MULTIWAVELET; COMPARATIVE STUDIES; CURVELET; DIRECTIONAL WAVELETS; DISCRETE TRANSFORMS; IMAGE PROCESSING APPLICATIONS; IMAGE TEXTURE ANALYSIS; LCD SCREENS; MULTIRIDGELETS; MULTIWAVELETS; MURA DEFECTS; NATURAL IMAGES; ORIENTATION SELECTIVITIES; POLAR ANGLES; RADON TRANSFORMS; RIDGELET; RIDGELETS; SCALAR WAVELETS; SPARSE REPRESENTATIONS; STANDARD DEVIATIONS; STATISTICAL FEATURES; TEXTURE ANALYSIS; TEXTURE ANALYSIS METHODS;

APPLICATIONS; FOURIER TRANSFORMS; IMAGE PROCESSING; IMAGING SYSTEMS; RADON; SUPPORT VECTOR MACHINES;

TEXTURES;

EID: 62649145070     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.805626     Document Type: Conference Paper

References (23)

1. E.J. Candes, "What is a Curvelet?," Notices of the American Mathematical Society, Volume 50, Number 11, pp. 1402-1403, 2003.
2. E.J. Candes, Ridgelets: Theory and Application, Ph.D. Thesis, Department of Statistics, Stanford University, 1998.
3. E.J. Candes and D.L. Donoho, "Curvelets - a Surprisingly Effective Nonadaptive Representation for Objects with Edges," Curves and Surfaces, L.L. Schumaker, A. Cohen, and C. Rabut, Nashville, TN, (Vanderbilt University Press), pp. 123-143, 1999.
4. M.N. Do and M. Vetterli, "The Contourlet Transform: An Efficient Directional Multiresolution Image Representation," IEEE Transaction on Image Processing, Volume 14, Number 12, pp. 2091-2106, December 2005.
5. V. Strela, P.N. Heller, G. Strang, P. Topiwala, and C. Heil, "The Application of Multiwavelet Filter Banks to Image Processing," IEEE Transaction on Image Processing, Volume 8, Number 4, pp. 548-562, April, 1999.
6. S.R. Deans, The Radon Transform and Some of Its Applications, Wiley, 1983.
7. Understanding pixel defects in TFT-LCD flat panel monitors, Hewlett-Packard Development Company, L.P. 5981-6351EN, 2004
8. J. Ryu, J. Oh, J. Kim, T. Koo, and K. Park, "TFT-LCD Panel Blob-Mura Inspection using The Correlation of Wavelet Coefficients," TENCON 2004. IEEE Region 10 Conference, vol. A, pp. 219 - 222, 2004.
9. A.B. Watson, "31.1: Invited Paper: The Spatial Standard Observer: A Human Vision Model for Display Inspection," SID Symposium Digest of Technical Papers, Vol. 37, Issue 1, pp. 1312-1315, June 2006.
10. A. Averbuch, R. R. Coifman, D. L. Donoho, M. Israeli, and J. Waldén, Fast Slant Stack: A notion of Radon Transform for Data in a Cartesian Grid which is Rapidly Computable, Algebraically Exact, Geometrically Faithful and Invertible, Technical Reports, 2001 [online] Available: http://www-stat.stanford.edu/~donoho/Reports/2001/FastSlantStack.pdf.
11. DL. Donoho and A.G. Flesia, Digital Ridgelet Transform based on True Ridge Functions, Technical Reports, 2001 [online] Available: http://www-stat.stanford.edu/~donoho/Reports/2001/DigRidgeTrue.pdf.
12. M.N. Do and Martin Vetterli, "The Finite Ridgelet Transform for Image Representation," IEEE Transaction on Image Processing, Volume 12, Number 1, pp 16-28, January 2003.
13. X.J. Jun, N. Lin, and Y. Miao, "A New Digital Implementation of Ridgelet Transform for Images of Dyadic Length," Proceedings of the Third International Conference on Information Technology and Applications, Volume 1, pp 613-616, July 2005.
14. I.W. Selesnick, "Interpolating Multiwavelet Bases and the Sampling Theorem," IEEE Transaction on Signal Processing, Volume 47, Number 6, pp. 1615-1621, June 1999.
15. V. Vapnik, The Nature of Statistical Learning Theory, Springer Verlag, 1995.
16. K.M. Rajpoot and N.M. Rajpoot, "Wavelets and Support Vector Machines for Texture Classification," Proceedings of INMIC, pp. 328-333, December 2004.
17. Y. Zhang and J. Zhang, "A Fuzzy Neural Network Approach for Quantitative Evaluation of Mura in TFT-LCD," International Conference on Neural Networks and Brain, Vol. 1, pp. 424-427, Oct. 2005.
18. Y. Song, D. Choi, and K. Park, "Morphological Blob-Mura Defect Detection Method for TFT-LCD Panel Inspection," Lecture Notes in Artificial Intelligence, Vol. 3215, pp. 862-868, 2004.
19. Video Electronics Standards Association (VESA): Flat Panel Display Measurements Standard, Ver. 2.0, p. 78.
20. M. Lanyi, Diagnosis and Differential Diagnosis of Breast Calcifications, Berlin: Springer-Verlag, 1988.
21. A. Barth, P.H. Craig, and M.J. Silverstein, "Predictors of Axillary Lymph Node Metastases in Patients with T1 Breast Carcinoma," Cancer, Vol. 79, No. 10, pp. 1918-1922, 1997.
22. M.T. Freedman, D.E. Steller Artz, H. Jafroudi, S.B. Lo, R.A. Zuurbier, R. Katial, W.S. Hayes, C.Y. Wu, J. Lin, R.M. Steinman, and W.G. Tohme, "Digital Mammography: Tradeoffs Between 50- and 100-micron pixel size," Proc. SPIE Vol. 2432 Image Quality and X-Ray Physics II, 114, 1995.
23. Y. Lee and O.L. Mangasarian, "SSVM: A Smooth Support Vector Machine," Computational Optimization and Applications, 20, 5-22. Data Mining Institute, University of Wisconsin, Technical Report 99-03. ftp://ftp.cs.wisc.edu/pub/dmi/techreports/99-03.ps.