Motion-free super-resolution

Motion-Free Super-Resolution

Volumn , Issue , 2005, Pages 1-239

  Chaudhuri, Subhasis ^a   Joshi, Manjunath V ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84892298157     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/b136446     Document Type: Book

References (218)

1. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Pearson Education, Inc, 2002.
2. E. L. Hall, Image Processing and Recognition, Academic Press, New York, 1979.
3. R. J. Schalkof, Digital Image Processing and Computer Vision, John Wiley, New York, 1989.
4. H. Stark and P. Oskui, "High-Resolution Image Recovery from Image-Plane Arrays Using Convex Projections, " J. Optical Society of America, vol, 6, no. 11, pp. 1715-1726, Nov. 1989.
5. K. Aizawa, T. Komatsu, and T. Saito, "A Scheme for Acquiring Very High Rerolution Images Using Multiple Cameras, " in Proc. IEEE Int. Conf. on Acoustics, Speech, Signal Processing, San Francisco, CA, 1992, pp. 289-292.
6. T. Komatsu, K. Aizawa, T. Igarshi, and T. Saito, "Signal Processing Based Method for Acquiring Very High Resolution Image with Multiple Cameras and its Theoretical Analysis, " in Proc. lEE-I, 1993, pp. 19-25.
7. D. Rajan, Some New Approaches to Generation of Super-Resolution Images, Ph.D. thesis, School of Biomedical Engineering, Indian Institute of Technology-Bombay, India, 2001.
8. N. Nguyen and P. Milanfar, "A Wavelet-Based Interpolation Restoration Method for Super-resolution, " Circuits, Systems and Signal Processing, Special issue on advanced signal and image reconstruction, vol. 19, no. 4, pp. 321-338, August 2000.
9. D. Rajan and S. Chaudhuri, "Generation of Super-Resolution Images from Blurred Observations using an MRF Model, " J. Mathematical Imaging and Vision, vol. 16, pp. 5-15, 2002.
10. M. Elad and A. Feuer, "Restoration of a Single Superresolution Image from Several Blurred, Noisy and Undersampled Measured Images, " IEEE Trans. on Image Processing, vol. 6, no. 12, pp. 1646-1658, December 1997.
11. D. Rajan and S. Chaudhuri, "Generalized Interpolation and its Appications in Super-Resolution imaging, " Image and Vision Computing, vol. 19, pp. 957-969, November 2001.
12. C. Delherm, J. M. Lavest, M. Dhome, and J. T. Lapreste, "Dense Reconstruction by Zooming, " in Fourth Europeon Conf on Computer Vision, Cambridge, England, April 1996, pp. 427-438.
13. J. M. Lavest, G. Rives, and M. Dhome, "Three Dimensional Reconstruction by Zooming, " IEEE Trans, on Robotics and Automation, vol. 9, no. 2, pp. 196-207, April 1993.
14. J. Ma and S. I. Olsen, "Depth from Zooming, " Journal of the American Optical Society, vol. 7, no. 10, pp. 1883-1890, October 1990.
15. D. Wilkes, S. J Dickinson, and J. K. Tsotsos, "A Quantitative Analysis of View Degeneracy and its use for Active Focal length Control, " in Proc. IEEE Int. Conf. on Computer Vision, Cambridge, Massachusetts, 1995, pp. 938-944.
16. J. A. Fayman, O. Sudarsky, and E. Rivlin, "Zoom Tracking and its Applications, " Tech. Rep. TR CIS9717, Technion-Israel Institute of Technology, December 1997.
17. M. V. Joshi and S. Chaudhuri, "Super-Resolution Imaging : Use of Zoom as a Cue, " in Indian Conf. on Computer Vision Graphics and Image Processing, Ahmedabad, 2002.
18. D. Rajan, S. Chaudhuri, and M. V. Joshi, "Multi-Objective Super-Resolution Technique : Concept and Examples, " IEEE Signal Processing Magazine, Special issue on Super-Resolution Image Reconstruction, vol. 20, no. 3, pp. 49-61, May 2003.
19. D. Rajan and S. Chaudhuri, "Simultaneous Estimation of Super-Resolved Scene and Depth map from Low Resolution Defocused Observations, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 25, no. 9, pp. 1102-1117, September 2003.
20. M. V. Joshi and S. Chaudhuri, "A Learning-Based Method for Image Super-Resolution from Zoomed Observations, " in Proc. fifth Int. Conf. on Advances in Pattern Recognition, Kolkata, India, 2003, pp. 179-182.
21. M.V. Joshi and S. Chaudhuri, "Photometric Stereo Under Blurred Observations, " in Proc. of IEEE Intl Conf. on Pattern Recognition, Cambridge, England, August, 2004.
22. C. V. Jiji, M. V. Joshi, and S. Chaudhuri, "Single Frame Image Super-Resolution using Learnt Wavelet Coefficients, " International Journal of Imaging Science and Technology, vol. 14, no. 3, pp. 105-112, September 2004.
23. M. V. Joshi and S. Chaudhuri, "Zoom Based Super-Resolution Through SAR Model Fitting, " in Proc. of IEEE Intl Conf. on Image Processing, Singapore, October, 2004.
24. C. V. Jiji and S. Chaudhuri, "PCA based Generalized Interpolation for Image Super-Resolution, " in Proc. of Indian Conf. on Vision, Graphics and Image Processing, Kolkata, India, December, 2004.
25. M. V. Joshi, S. Chaudhuri, and R. Panuganti, "Super-Resolution Imaging: Use of Zoom as a Cue, " Image and Vision Computing, vol. 22, no. 14, pp. 1185-1196, December 2004.
26. M. V. Joshi and S. Chaudhuri, "Joint Blind Restoration and Surface Recovery in Photometric Stereo, " Journal of Optical Society of America-A (Accepted for publication).
27. M. V. Joshi, S. Chaudhuri, and R. Panuganti, "A Learning-Based Method for Image Super-Resolution from Zoomed Observations, " IEEE Trans. Systems Man and Cybernetics, PART B, Special Issue on Learning in Computer Vision and Pattern Recognition (Accepted for publication).
28. S. Chaudhuri, (Ed.), Super-Resolution Imaging, Kluwer Academic Publisher, Boston, 2001.
29. S. C. Park, M. K. Park, and M. G. Kang, "Super-Resolution Image Reconstruction: A Technical Review, " IEEE Signal Processing Magazine, Special Issue of Super-resolution Image Reconstruction vol. 20, no. 3, pp. 21-36, May 2003.
30. R. Y. Tsai and T. S. Huang, "Multiframe Image Restoration and Registration, " in Advances in Computer Vision and Image Processsing, pp. 317-339. JAI Press Inc., 1984.
31. S. P. Kim, N, K. Bose, and H. M. Valenzuela, "Recursive Reconstruction of High Resolution Image From Noisy Undersampled Multiframes, " IEEE Trans. on Accoustics, Speech and Signal Processing vol. 38, no. 6, pp. 1013-1027, June 1990.
32. S. P. Kim and W. Y. Su, "Recursive High Resolution Reconstruction of Blurred Multiframe Images, " IEEE Trans, on Image Processing vol. 2, no. 4, pp. 534-539, October 1993.
33. S. H. Rhee and M. G. Kang, "Discrete Cosine Transform based Regularized High Resolution Image Reconstruction Algorithm, " Optical Engineering, vol. 38, no. 8, pp. 1348-1356, August 1999.
34. C. Srinivas and M. D. Srinath, "A Stochastic Model based Approach for Simultaneous Restoration of Multiple Mis-registered Images, " Proc, SPIE, vol. 1360, pp. 1416-1427, 1990.
35. A. Papoulis, "Generalized Sampling Theorem, " IEEE Trans, on Circuits and Systems, vol. 24, pp. 652-654, November 1977.
36. J. L. Brown, "Multi-Channel Sampling of Low Pass Signals, " IEEE Trans, on Circuits and Systems, vol. CAS-28, no. 2, pp. 101-106, February 1981.
37. H. Ur and D. Gross, "Improved Resolution from Sub-pixel Shifted Pictures, " CVG IP Graphical Models and Image Processing, vol. 54, pp. 181-186, March 1992.
38. N. K. Bose, H. C. Kim, and H. M. Valenzuela, "Recursive Implementation of Total Least Squares Algorithm for Image Reconstruction from Noisy, Undersampled Multiframes, " in In Proc. of IEEE Conference on Acoustics, Speech and Signal Processing, Minneapolis, MN, 1993, pp. 269-272.
39. M. Irani and S. Peleg, "Improving Resolution by Image Registration, " CVG IP: Graphical Models and Image Processing, vol. 53, pp. 231-239, March 1991.
40. S. Peleg, D. Keren, and L. Schweitzer, "Improving Image Resolution using Sub-pixel Motion, " Pattern Recognition. Letters., vol. 5, pp. 223-226, March 1987.
41. M. Irani and S. Peleg, "Motion Analysis for Image Enhancement : Resolution, Occlusion, and Transparency, " Journal of Visual Communication and Image Representation, vol. 4, pp. 324-335, December 1993.
42. A. M. Tekalp, M. K. Ozkan, and M. I. Sezan, "High Resolution Image Reconstruction from Lower-Resolution Image Sequences and Space-Varying Image restoration, " in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, San Francisco, USA, 1992, pp. 169-172.
43. M. K. Ng, N. K. Bose, and J. Koo, "Constrained Total Least Squares Computation for High Resolution Image Reconstruction with Multisensors, " International Journal of Imaging Systems and Technology, vol. 12, pp. 35-42, 2002.
44. M. K. Ng and N. K. Bose, "Analysis of Displacement Errors in High Resolution Image Reconstruction with Multisensors, " IEEE Trans, on Circuits and Systems 1: Fundamental Theory and Applications vol. 49, no. 6, pp. 806-813, June 2002.
45. N. K. Bose, S. Letrattanapanich, and J. Koo, "Advances in Super-resolution Using L Curve, " in Proc. Int. Symp. Circuits and Systems Sydney, 2001, pp. 433-436.
46. P. C. Hansen and D. Prost O'Leary, "The Use of the L-Curve in Regularization of Discrete Ill-posed Problems, " SIAM J. Sci. Comput, vol. 14, no. 6, pp. 1487-1503, November 1993.
47. R. C. Hardie, K. J. Barnard, and E. E. Armstrong, "Joint MAP Registration and High-Resolution Image Estimation Using a Sequence of Undersampled Images, " IEEE Trans, on Image Processing vol. 6, no. 12, pp. 1621-1633, December 1997.
48. R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, "Joint High Resolution Image Reconstruction from a Sequence of Rotated and Translated Frames and its Application to an Infrared Imaging System, " Optical Engineering, vol. 37, pp. 247-260, January 1998.
49. N. A. Woods, N. A. Galatsanos, and A. K. Katsaggelos, "EM-based Simultaneous Registration, Restoration, and Interpolation of Super-resolved Images, " in Proc. IEEE Int. Conf. on Image Processing, Barcelona, Spain, 2003.
50. R. R. Schultz and R. L. Stevenson, "A Bayesian Approach to Image Expansion for Improved Definition, " IEEE Trans, on Image Processing, vol. 3, no. 3, pp. 233-242, May 1994.
51. N. Nguyen, P. Milanfar, and G. Golub, "Efficient Generalized Cross-Validation with Applications to Parametric Image Restoration and Resolution Enhancement, " IEEE Trans, on Image Processing, vol. 10, no. 9, pp. 1299-1308, September 2001.
52. N. Nguyen, P. Milanfar, and G. Golub, "A Computationally Efficient Superresolution Reconstruction Algorithm, " IEEE Trans, on Image Processing, vol. 10, no. 4, pp. 573-583, April 2001.
53. M. Elad and A. Feuer, "Super-Resolution Restoration of an Image Sequence : Adaptive Filtering Approach, " IEEE Trans, on Image Processing, vol. 8, no. 3, pp. 387-395, March 1999.
54. M. Elad and Y. Hel-Or, "A Fast Super-resolution Reconstuction Algorithm for Pure Translation Motion and Common Space-Invariant Blur, " IEEE Trans. on Image Processing, vol. 10, no. 8, pp. 1187-1193, August 2001.
55. P. Jorge and S. G. Ferreira, "Two Fast Extrapolation/Super- Resolution Algorithms, " in Proc. IEEE Int. Conf. on Image Processing, Vancouver, British Columbia, 2000, pp. 343-346.
56. J. H. Shin, J. S. Yoon, J. K. Paik, and M. abidi, "Fast Super-Resolution for Image Sequences using Motion Adaptive Relaxation Parameters, " in Proc. IEEE Int. Conf. on Image Processing, Kobe, Japan, 1999, pp. 676-680.
57. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, "Fast and Robust Superresolution, " in Proc. IEEE Int. Conf. on Image Processing, Barcelona, Spain, 2003.
58. A. Lorette, H. Shekarforoush, and J. Zerubia, "Super-Resolution with Adaptive Regularization, " in Proc. IEEE Int. Conf. on Image Processing, Santa Barbara, California, 1997, pp. 169-172.
59. P. Charbonnier, Reconstruction image: regularisation avec prise en compte des discontinuities, Ph.D. thesis, UNSA, September 1994.
60. T. Hebert, and R. Leahy, "A Generalized EM algorithm for 3D Bayesian Reconstruction from Poisson Data Using Gibb's Prior, " IEEE Trans, on Medical Imaging, vol. MI-8, pp. 194-202, June 1989.
61. D. Geman and G. Reynolds, "Constrained Restoration and the Recovery of Discontinuities, " IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 14, no. 3, pp. 367-383, March 1992.
62. M. C. Chiang and T. E. Boult, "Local Blur Estimation and Super-Resolution, " in Proc. IEEE Int. Conf. Computer Vision and Pattern Recognition, Puerto Rico, USA, 1997, pp. 821-826.
63. M. C. Chiang and T. E. Boult, "Efficient Super-Resolution via Image Warping, " Image and Vision Computing, vol. 18, pp. 761-771, December 2000.
64. M. C. Chiang and T. E. Boult, "The Integrating Resampler and Efficient Image Warping, " in Proc. of the DARPA Image Understanding Workshop, 1996, pp. 843-849.
65. A. Zomet, A. Rav-Acha, and S. Peleg, "Roboust Super-Resolution, " in Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, Kauai, HI, USA, 2001, pp. 645-650.
66. S. Zhao, H. Han, and S. Peng, "Wavelet-Domain HMT-Based Image Superresolution, " in Proc. IEEE Int. Conf. on Image Processing, Barcelona, Spain, 2003.
67. S. C. Park, M. G. Kang, C. A. Segall, and A. K. Katsaggelos, "Spatially Adaptive High Resolution Image Reconstruction of Low Resolution DCT based Compressed Images, " in Proc. IEEE Int. Conf. on Image Processing, Rochester, New York, September, 2002.
68. C. A. Segall, R. Molina, A. K. Katsaggelos, and J. Mateos, "Reconctructon of High Resolution Image Frames from a Sequence of Low Resolution and Compressed Observations, " in Proc. IEEE Int. Conf. on Acoustics Speech and Signal Processing, Florida, May, 2002, pp. 1701-1704.
69. Z. Lin and H. Y. Shum, "Fundamental Limits of Reconstruction-Based Super-Resolution Algorithms Under Local Translation, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 26, no. 1, pp. 83-97, January 2004.
70. D. R. Gerswe and M. A. Plonus, "Superresolved Image Reconstruction of Images taken through the Turbulant Atmosphere, " Journal of the Optical Society of America, vol. 15, no. 10, pp. 2620-2628, October 1998.
71. Q. Yang and B. Parvin, "High Resolution Reconstruction of Sparse Data from Dense Low Resolution Spatio-Temporal Data, " IEEE. Trans, on Image Processing, vol. 12, no. 6, pp. 671-677, June 2003.
72. B. K. Gunturk, A. U. Batur, Y. Altunbasak, M. H. Hayes HI, and R. M. Mersereau, "Eigenface Based super-resolution for Face Recognition, " in Proc. IEEE Int. Conf. on Image Processing, Rochester, New York, 2002, pp. 845-848.
73. B. K. Gunturk, A. U. Batur, Y. Altunbasak, M. H. Hayes III, and R. M. Mersereau, "Eigenface-Domain Super-resolution for Face Recognition, " IEEE Trans, on Image Processing, vol. 12, no. 5, pp. 597-606, May 2003.
74. D. Capel and A, Zisserman, "Super-Resolution Enhancement of Text Image Sequences, " in Proc. IEEE Int. Conf. on Pattern Recognition, Barcelona, Spain, 2000, pp. 600-605.
75. U. Bhosle, S. Gavali, and S. Chaudhuri, "Super-Mosaicing: Mosaicing at High Resolution, " in Proc. Tenth National Conf. on Communications, Indian Institute of Science, Bangalore, 2004, pp. 106-110.
76. A. Zomet and S. Peleg, "Efficient Super-resolution and Applications to Mosaics, " in Proc. IEEE Int. Conf. on Pattern Recognition, Barcelona, Spain, 2000, pp. 579-583.
77. D. Capel and A. Zisserman, "Automated Mosaicing with Super-resolution Zoom, " in Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, Santa Barbara, 1998, pp. 885-891.
78. A.J. Patti, M. I. Sezan, and A. M. Tekalp, "Superresolution Video Reconstruction with Arbitrary Sampling Lattices and Nonzero Aperture Time, " IEEE TYans. on Image Processing, vol. 6, no. 8, pp. 1064-1076, August 1997.
79. P. E. Eren, M. I. Sezan, and A. M. Tekalp, "Robust Object based Highresolution Image Reconstruction from Low Resolution Video, " IEEE Trans. on Image Processing, vol. 6, no. 10, pp. 1446-1451, October 1997.
80. A. J. Patti, M. I. Sezan, and A. M. Tekalp, "Robust Methods for High-Quality Stills from Interlaced Video in the Presence of Dominant Motion, " IEEE Trans. on Circuits and systems For Video Technology, vol. 7, no. 2, pp. 328-342, April 1997.
81. R. R. Schultz and R. L. Stevenson, "Extraction of High-Resolution Frames from Video Sequences, " IEEE Trans, on Image Processing, vol. 5, no. 6, pp. 996-1011, June 1996.
82. N. R. Shah and A. Zakhor, "Resolution Enhancement of Color Video Sequences, " IEEE Trans, on Image Processing vol. 8, no. 6, pp. 879-885, June 1999.
83. M. C. Hong, M. G. Kang, and A. K. Katsaggelos, "A Regularized Multichannel Restoration Approach for Globally Optimal High Resolution Video Sequence, " in Proc. SPIE Conf. on Visual Communications and Image Processing San Jose, CA, USA, 1997, pp. 1306-1316.
84. B. C. Tom and A. K. Katsaggelos, "Resolution Enhancement of Monochrome and Color Video Using Motion Compensation, " IEEE Trans, on Image Processing, vol. 10, no. 2, pp. 279-287, February 2001.
85. Y. Altunbask, A. J. Patti, and R. M. Mersereau, "Super-Resolution Still and Video Reconstruction From MPEG-Coded Video, " IEEE Trans, on Circuits and Systems for Video Technology, vol. 12, no. 4, pp. 217-226, april 2002.
86. C. A. Segall, R. Molina, A. K. Katsaggelos, and J. Mateos, "Bayesian High-Resolution Reconstruction of Low-Resolution Compressed video, " in Proc. IEEE Int. Conf Image Processing, Thessaloniki, Greece, 2001, pp. 25-28.
87. S. Chaudhuri and D. Taur, "High Resolution Slow Motion Sequencing, " IEEE Signal Processing Magazine (Special Issue on Visual Surveillance), Jan 2005.
88. H. Shekarforoush and R. Chellappa, "Data-driven Multichannel Super-Resolution with Applications to Video Sequences., " Journal of the Optical Society of America A, vol. 16, no. 3, pp. 481-492, 1999.
89. S. Borman and R. L. Stevenson, "Simultaneous Multi-frame MAP Super-Resolution Video Enhancement using Spatio-temporal Priors, " in Proc. IEEE Int. Conf. on Image Processing, Kobe, Japan, October 1999, pp. 469-473.
90. Z. Wang and F. Qi, "Super-Resolution with Model Uncertainties, " in Proc. IEEE Int. Conf. on Image Processing, Rochester, New York, 2002, pp. 853-856.
91. B. K. Gunturk, Y. Altunbasak, and R. Mersereau, "Bayesian Resolution-Enhancement Framework for Transform-Coded Video, " in Proc. IEEE Int. Conf. on Image Processing, Thessaloniki, Greece, 2001, pp. 41-44.
92. E. Shechtman, Y. Caspi, and M. Irani, "Increasing Space-Time Resolution in Video, " in European Conference on Computer Vision, Copenhagen, 2002, pp. 753-769.
93. D. Rajan and S. Chaudhuri, "Generation of Super-resolution Images from Blurred Observations using an MRF Model, " J. Mathematical Imaging and Vision, vol. 16, pp. 5-15, 2002.
94. A. N. Rajagopalan and V. P. Kiran, "Motion-free Super-Resolution and the Role of Relative Blur, " Journal of the Optical Society of America A, vol. 20, no. 11, pp. 2022-2032, November 2003.
95. I. Zakharov, D. Dovanar, and Y. Lebedinsky, "Super-Resolution Image Restoration from Several Blurred Images formed in Various Conditions, " in Proc. IEEE Int. Conf. on Image Processing, Barcelona, Spain, 2003.
96. D. Rajan and S. Chaudhuri, "Generalized Interpolation for Super-Resolution, " in Super-Resolution Imaging, S. Chaudhuri, Ed., pp. 45-72. Kluwer Academic Publisher, Boston, 2001.
97. W. T. Freeman, T.R.Jones, and E. C.Pasztor, "Example-Based Super-Resolution, " IEEE Computer Graphics and Applications, vol. 22, no. 2, pp. 56-65, March/april 2002.
98. D. Capel and A. Zisserman, "Super-Resolution from Multiple Views Using Learnt Image Models, " in Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, Kauai, HI, USA, 2001, pp. 627-634.
99. L. C. Pickup, S. J. Roberts, and A. Zisserman, "A Sampled Texture Prior for Image Super-Resolution, " in In Proc. of Advances in Neural Information Processing Systems, 2003.
100. S. Baker and T. Kanade, "Limits on Super-Resolution and How to Break Them, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 24, no. 9, pp. 1167-1183, September 2002.
101. A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin, "Image Analogies, " in Proc. ACM-SIGGRAPH, 2001, pp. 327-340.
102. F. M. Candocia and J. C. Principe, "Super-Resolution of Images based on Local Correlations, " IEEE Trans, on Neural Networks, vol. 10, no. 2, pp. 372-380, March 1999.
103. C. M. Bishop, A. Blake, and B. Marthi, "Super-Resolution Enhancement of Video, " in Int. Conf. on Artificial Intelligence and Statistics, Key West, Florida, 2003.
104. A. P. Pentland, "Depth of Scene from Depth of Field, " in Proc. of Image Understanding Workshop, Palo Alto, USA, 1982, pp. 253-259.
105. S. Chaudhuri and A. N. Rajagopalan, From Defocus: A Real Aperture Imaging Approach, Springer-Verlog, New York, 1999.
106. M. Subbarao, "Efficient Depth Recovery Through Inverse Optics, " in Machine Vision for Inspection and Measurement, H. Freeman, Ed. Academic Press, 1989.
107. A. P. Pentland, "A New Sense for Depth of Field, " IEEE Trans, on Pattern Anal, and Machine Intel, vol. 9, no. 4, pp. 523-531, July 1987.
108. M. Born and E. Wolf, Principles of Optics, Pergamon, London, 1965.
109. M. Subbarao, "Parallel Depth Recovery by Changing Camera Parameters, " in Proc. International Conference on Computer Vision Florida, USA, 1988, pp. 149-155.
110. K. V. Prasad, R. J. Mammone, and J. Yogeshwar, "3-D Image Restoration using Constrained Optimization Techniques, " Optical Engineering vol. 29, no. 4, pp. 277-288, April 1990.
111. W. N. Klarquist, W. S. Geisler, and A. C. Bovik, "Maximum-Likelihood Depthfrom-Defocus for Active Vision, " in Proc. of IEEE Intl. Conf. on Intelligent Robots and Systems Pittsburgh, PA, 1995.
112. M. Gokstorp, "Computing Depth from Out-of-Focus Blur Using a Local Frequency Representation, " in Proc. of IEEE Intl. Conf. on Pattern Recognition Jerusalem, Israel, 1994, pp. 153-158.
113. M. Watanabe and S. K. Nayar, "Minimal operator set for passive DFD, " in Proc. of IEEE Intl. Conf.on Computer Vision and Pattern Recognition San Francisco, CA, 1996, pp. 153-158.
114. Y. Y. Schechner and N. Kiryati, "Depth from Defocus vs Stereo: How Different Really are They?, " Tech. Rep. EE PUB No. 1155, Technion-Israel Institute of Technology, May 1998.
115. S. K. Nayar, M. Watanabe, and M. Noguchi, "Real-time Focus Range Sensor, " IEEE Trans, on Pattern Analysis and Machine Intelligence vol. 18, no. 12, pp. 1186-1198, Dec. 1996.
116. A. N. Rajagopalan and S. Chaudhuri, "Space-variant approaches to recovery of depth from defocused images, " Computer Vision and Image Understanding vol. 68, no. 3, pp. 309-329, Dec. 1997.
117. A. N. Rajagopalan and S. Chaudhuri, "A Variational Approach to Recovering Depth from Defocused Images, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 19, no. 10, pp. 1158-1165, Oct. 1997.
118. A. N. Rajagopalan and S. Chaudhuri, "An MRF Model Based Approach to Simultaneous Recovery of Depth and Restoration from Defocused Images, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 21, pp. 577-589, July 1999.
119. H. Shekarforoush, M. Bertod, J. Zerubia, and M. Werman, "Sub-pixel Bayesian Estimation of Albedo and Height, " International Journal of Computer Vision, vol. 19, no. 3, pp. 289-300, 1996.
120. P. Cheeseman, B. Kanefsky, R. Hanson, and J. Stutz, "Super-Resolved Surface Reconstruction from Multiple Images, " Tech. Rep. FIA-94-12, NASA Ames Research center, Mofett Field, CA, December 1994.
121. E. Ising, "Beitag Sur Theorie Des Ferromegnetisms, " Zeitschrift Physik, vol. 31, pp. 253-258, 1925.
122. R. C. Dubes and A. K. Jain, "Random Field Models in Image Analysis, " Journal of Applied Statistics, vol. 16, no. 2, pp. 131-164, 1989.
123. J. Besag, "Spatial Interaction and the Statistical Analysis of Lattice Systems, " Journal of Royal Statistical Society Series B, vol. 36, pp. 192-236, 1974.
124. S. Geman and D. Geman, "Stochastic Relaxation, Gibbs distribution and the Bayesian restoration of image, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 6, no. 6, pp. 721-741, 1984.
125. J. Subrahmonia, Y.P Hung, and D. B. Cooper, "Model Based Segmentation and Estimation of 3D Surfaces from Two or More Intensity Images Using Markov Random Fields, " in Proc. of IEEE Intl. Conf. on Pattern Recognition, Atlantic Citys, USA, 1990, pp. 390-397.
126. D. B. Cooper, J. Subrahmonia, Y.P. Hung, and B. Cernuschi-Frias, "The Use of Markov Random Fields in Estimating and Recognizing Objects in 3D Space, " in Markov Random Fields : Theory and applications R. Chellappa and A. Jain, Eds., pp. 335-368. Academic Press, 1993.
127. S. Lakshmanan and H. Derin, "Gaussian Markov Random Fields at Multiple Resolutions, " in Markov Random Fields, Theory and Application R. Chellappa and A. K. Jain, Eds., pp. 131-157. Academic Press, Inc, 1993.
128. E. H. Adelson and J. R. Bergen, "The Plenoptic Function and the Elements of Early Vision, " in Computational Models of Visual Processing, M. Landy and J. A. Movshon, Eds., pp. 3-20. Cambridge, MA:MIT Press, 1991.
129. T. Wong, C. Fu, P. Heng, and C. Leung, "The Plenoptic Illumination Function, " IEEE Trans, on Multimedia, vol. 4, no. 3, pp. 361-371, September 2002.
130. M. Berthod, H. Shekarforoush, M. Verman, and J. Zerubia, "Reconstruction of High Resolution 3D Visual Information, " Tech. Rep. RR-2142, INRIA, November 1993.
131. H. Shekarforoush, M. Berthod, and J. Zerubia, "3D Super-Resolution Using Generahsed Sampling Expansion, " in Proc, IEEE Int. Conf. on Image Processing, Washington DC, 1995, pp. 300-303.
132. Y. P. Hung and D. B. Cooper, "Maximum a Posteriori Probability 3D Surface Reconstruction Using Multiple Intensity Images Directly, " SPIE, vol. 1260, pp. 36-48, 1990.
133. S. G. Deshpande and S. Chaudhuri, "Recursive Estimation of Illuminant Motion from Flow Field and Simultaneous Recovery of Shape, " Computer Vision and Image Undersatanding, vol. 72, no. 1, pp. 10-20, October 1998.
134. A. N. Tikhonov and V. Y. Arsenin, Solutions of Ill-posed Problems, W. H. Winston, Washington D. C, 1977.
135. A. N. Tikhonov, "Solution of Incorrectly Formulated Problems and the Regularization method, " in Soviet Math. Dokl, 1963, pp. 1035-1038.
136. M. Bertero, "Regularization Methods for Linear Inverse Problems, " in Inverse Problems, C. G. Talenti, Ed. Springer Verlog, Berlin, 1986.
137. V. A. Morozov, Methods for Solving Incorrectly Posed Problems, Springer-Verlag, Berlin, 1984.
138. B. K. P Horn, Robot Vision, MIT Press, 1986.
139. B. K. P. Horn, Shape from Shading: A Method for Obtaining the Shape of a Smooth Opaque Object from One View, Ph.D. thesis, Massachussetts Inst, of Technology, 1970.
140. K. Ikeuchi and B. K. P. Horn, "Numerical Shape from Shading and Occluding Boundaries, " Artificial Intelligence, vol. 17, no. 1-3, pp. 141-184, 1981.
141. A. P. Pentland, "Local Shading Analysis, " IEEE Trans. Pattern analysis and Machine Intelligence, vol. 6, no. 2, pp. 170-187, 1984.
142. A. P. Pentland, "Shape Information from Shading: A Theory about Human Perception, " in Proc. IEEE Intl. Conf. on Computer Vision, Florida, USA, 1988, pp. 404-413.
143. P. S. Tsai and M. Shah, "Shape from Shading Using Linear Approximation, " Image and Vision Computing, vol. 12, no. 8, pp. 487-498, 1994.
144. R. J. Woodham, "Reflectance Map Techniques for Analyzing Surface Defects in Metal Castings, " Tech. Rep. 457, MIT AI Lab, June 1978.
145. R. J. Woodham, "Photometric Method for Determining Surface Orientation from Multiple Images, " Optical Engineering, vol. 19, no. 1, pp. 139-144, 1980.
146. W. M. Silver, "Determining Shape and Reflectance Using Multiple Images, " M.S. thesis, DePARTment of Electrical and Computer Science, MIT, Cambridge, 1980.
147. K. Ikeuchi, "Determining Surface Orientations of Specular Surfaces by Using the Photometric Stereo Method, " IEEE Trans, on Pattern analysis and Machine Intelligence vol. 3, no. 6, pp. 661-669, 1981.
148. K. M. Lee and C. C. Jay Kuo, "Shape Reconstruction from Photometric Stereo, " in Proc. International Conf. on Computer Vision and Pattern Recognition, Champaign, Illinois, USA, 1992, pp. 479-484.
149. C. Y. Chen, R. Klette, and R. Kakarala, "Albedo Recovery Using a Photometric Stereo Approach, " in Proc. International Conference on Pattern Recognition, Quebec, Canada, 2002, pp. 700-703.
150. Y. Iwahori, R. J. Woodham, M. Ozaki, H. Tanaka, and N. Ishi, "Neural Network based Photometric Stereo with a Nearby Rotational Moving Light Source, " lEICE Transactions on Information and Systems, vol. E-80, no. 9, pp. 948-957, 1997.
151. Y. Iwahori, R. J. Woodhan, and A. Bagheri, "Principal Component Analysis and Neural Network Implementataion of Photometric Stereo, " in IEEE Workshop on Physics based Modeling in Computer Vision, Boston, MA, 1995, pp. 117-125.
152. R. J. Woodham, "Gradient and Curvature from the Photometric Stereo Method including Local Confidence Estimation, " Journal of the Optical Society of America-A, vol. 11, no. 11, pp. 3050-3068, 1994.
153. Y. Iwahori, R. J. Woodham, Y. Watanabe, and A. Iwata, "Self Calibration and Neural Network Implementation of Photometric Stereo, " in Proc. International Conf. on Pattern Recognition, Quebec, Canada, 2002, pp. 359-362.
154. O. Drbohlav and R. Sara, "Unambiguous Determination of Shape from Photometric Stereo with Unknown Light Sources, " in Proc. International Conf. on Computer Vision, Vancouver, BC, Canada, 2001, pp. 581-586.
155. R. Basri and D. Jacobs, "Photometric Stereo with General Unknown Lighting, " in Proc. International Conf. on Computer Vision and Pattern Recognition, Kauai, Hawaii, 2001, pp. 374-381.
156. U. Sakarya and I. Erkmen, "An Improved Method of Photometric Stereo Using Local Shape from Shading, " Image and Vision Computing, vol. 21, no. 11, pp. 941-954, 2003.
157. J. J. Clark, "Active Photometric Stereo, " in Proc. International Conf. on Computer Vision and Pattern Recognition, Champaign, Illinois, USA, 1992, pp. 29-34.
158. J. R. A. Torreao, "A New Approach to Photometric Stereo, " Pattern Recognition Letters, vol. 20, no. 5, pp. 535-540, 1999.
159. G. McGunnigle and M. J. Chantler, "Rotation Invariant Classification of Rough Surfaces, " lEE Proc. Vis. Image Signal Process, vol. 146, 1999.
160. G. McGunnigle and M.J. Chantler, "Rough Surface Classification Using Point Statistics from Photometric Stereo, " Pattern Recognition Letters, vol. 21, no. 6-7, pp. 593-604, 2000.
161. G. McGunnigle and M. J. Chantler, "Modelling Deposition of Surface Texture, " Electron. Letters, vol. 37, pp. 749-750, 2001.
162. M. L. Smith, T. Hill, and G. Smith, "Gradient Space analysis of Surface Defects Using a Photometric Stereo Derived Bump Map, " Image and Vision Computing, vol. 17, no. 3-4, pp. 321-332, 1999.
163. P. Hansson and P. Johansson, "Topography and Reflectance Analysis of Paper Surfaces Using Photmetric Stereo Method, " Optical Engineering vol. 39, pp. 2555-2561, 2000.
164. G. McGunnigle and M. J. Chantler, "Segmentation of Machined Surfaces, " in Irish Machine Vision and Image Processing Conference 2001, pp. 200-207.
165. M. R. Banham and A. K. Katsaggelos, "Digital Image Restoration, " IEEE Signal Processing Magazine, vol. 14, no. 2, pp. 24-41, 1997.
166. D. Kundur and D. Hatzinakos, "Blind Image Deconvolution, " IEEE Signal Processing Magazine, vol. 13, no, 3, pp. 43-64, 1996.
167. Y. You and M. Kaveh, "A Regularization Approach to Joint Blind Identification and Image Restoration, " IEEE Trans, on Image Processing, vol. 5, pp. 416-428, March 1996.
168. R. L. Lagendijk and J. Biemond, Iterative Identification and Restoration of Images, Kluwer Academic Publishers, 1991.
169. R. L. Lagendijk, J. Biemond, and D. E. Boekee, "Identification and Restoration of Noisy Blurred Images Using the Expectation Maximization Algorithm, " IEEE TYans. Acoustics, Speech and Signal Processing, vol. 38, no. 7, pp. 1180-1191, July 1990.
170. K. T. Lay and A. K. Katsaggelos, "Image Identification and Restoration based on the Expectation Maximization Algorithm, " Optical Engineering, vol. 29, pp. 436-445, May 1990.
171. M. K. Ozkan, A. M. Tekalp, and M. I. Sezan, "POCS based Restoration of Space Varying Blurred Images, " IEEE Trans. Image Processing, vol. 3, pp. 450-454, July 1995.
172. M. I. Sezan and A. M. Tekalp, "Iterative Image Restoration with Ringing Supression Using POCS, " in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing, Tokyo, 1988, pp. 1300-1303.
173. M.I. Sezan and H. J. Trussell, "Prototype Image Constraints for Set Theoretic Image Restoration, " IEEE trans. Acoustics, Speech and Signal Processing, vol. 39, no. 10, pp. 2275-2285, October 1991.
174. H. J. Trussell and M. R. Civanlar, "The Feasible Solution in Signal Restoration, " IEEE Trans, on Acoustics, Speech and Signal Processing, vol. 32, no. 2, pp. 201-212, April 1984.
175. Y. Yang, N. P. Galatsanos, and A. K. Katsaggelos, "Projection-based Spatially Adaptive Reconstruction of Block-Transform Compressed Images, " IEEE TYans. on Image Processing, vol. 4, no. 7, pp. 896-908, July 1995.
176. V. F. Candela, A. Marquina, and S. Serna, "A Local Spectral Inversion of a Linearized TV Model for Denoising and Deblurring, " IEEE TYans. on Image Processing, vol. 12, no. 7, pp. 808-816, 2003.
177. B. Besserer L. Joyeux, S. Boukir and O. Buisson, "Reconstruction of Degraded Image Sequences. Application to Film Restoration, " Image and Vision Computing, vol. 19, no. 8, pp. 503-516, 2001.
178. L. Bedini, A, Tonazzini, and S. Minutoli, "Unsupervised Edge-Preserving Image Restoration Via a Saddle Point Approximation, " Image and Vision Computing, vol. 17, no. 11, pp. 779-793, 1999.
179. T. F. Chan and C. K. Wong, "Convergence of the Alternating Minimization Algorithm for Bhnd Deconvolution, " Tech. Rep. 19, UCLA Computational and Applied Mathematics, June CAM99.
180. N. Kaulgud, J. Karlekar, and U. B. Desai, "Compressed Domain Video Zooming : Use of Motion Vectors, " in Proc. Eighth National Conf. on Communications Mumbai, India, Jan. 2002, pp. 120-124.
181. S. Thurnhofer and S. K. Mitra, "Edge-Preserving Image Zooming, " Optical Engineering, vol. 35, no. 7, pp. 1862-1870, 1996.
182. F. Malagouyres and F. Guichard, "Edge Direction Preserving Image Zooming: A Mathematical and Numerical Analysis, " SI AM Journal on Numerical Analysis, vol. 39, no. 1, pp. 1-37, 2001.
183. C. S. Burrus, R. A. Gopinath, and H. Guo, Introduction to Wavelets and Wavelet Transforms, Prentice Hall, New Jersy, 1998.
184. I. Daubechies, Ten Lectures on Wavelets, SIAM, Philadelphia, Pennsylvania, 1992.
185. A. Jensen and A. Cour-Harbo, Ripples in Mathematics: The Discrete Wavelet Transform, Springer-Verlag, 2001.
186. H. M. Shapiro, "Embedded Image Coding, " IEEE Trans, on Signal Processing, vol. 41, no. 12, pp. 3445-3462, December 1993.
187. E. J. Cands and D. L. Donoho, "Curvelets-A Surpisingly Effective Nonadaptive Representation for Objects with Edges, " in Curve and Surface Fitting, A. Cohen, C. Rabut, and L. L. Schumaker, Eds. Saint-Malo: Vanderbilt University Press, 1999.
188. M. N. Do, Directional Multiresolution Image Representations, Ph.D. thesis, Swiss Federal Institute of Technology, Lausanne, Switzerland, 2001.
189. D. L. Donoho, "Wedgelets: Nearly Minimax Estimation of Edges, " Ann. Statist, vol. 27, no. 3, pp. 859-897, 1999.
190. A. Cohen and B. Matei, "Compact Representation of Images by Edge Adapted Multiscale Transforms, " in IEEE Int. Conf. on Image Processing, Invited paper, Greece, October, 2001.
191. E. J. Cands and D. L. Donoho, "Ridgelets: A Key to Higher Dimensional Intermittency, " Phil. Trans. R. Soc. Lond. A., vol. 357, pp. 2495-2509, 1999.
192. M. Turk and A, Pentland, "Eigenfaces for Recognition, " J. of Cognitive Neuroscience, vol. 3, no. 1, pp. 71-86, 1991.
193. G. F. Carey, Computational Grids: Generation Adaptation and Solution Strategies, Taylor and Francis, 1997.
194. M. J. D. Powell, "The Uniform Convergence of Thin Plate Spline Interpolation in Two Dimensions, " Numerishce Mathematik, vol. 68, pp. 107-128, 1994.
195. P. Dani and S. Chaudhuri, "Automated Assembling of Images: Image Montage Preparation, " Pattern Recognition, vol. 28, no. 3, pp. 431-445, March 1995.
196. Hong Jing and Liudi Liu, "Color Space Conversion Methods' Applications to the Image Fusion, " Optical Technology, no. 4, pp. 44-48, 1997.
197. P. S. Jr. Chavez, S. C. Sides, and J. A. Anderson, "Comparison of Three Different Methods to Merge Multiresolution and Multispectral Data: Landsat TM and SPOT Panchromatic, " Photogrammetric Engineering and Remote Sensing, vol. 57, no. 3, pp. 295-303, 1991.
198. M. Ehlers, "Multisensor Image Fusion Techniques in Remote Sensing, " ISPRS Journal of Photogrammetry and Remote Sensing, vol. 46, pp. 19-30, 1991.
199. Eryong Yu and Runsheng Wang, "Fusion and Enhancement of the Multispectral Image with Wavelet Transform, " Computer Engineering and Science, vol. 23, no. 1, pp. 47-50, 2001.
200. B. Aiazzi, L. alparone, S. Baronti, and A. Garzelli, "Context Driven Fusion of High Spatial and Spectral resolution Images based on Oversampled Multiresolution Analysis, " IEEE trans, on Geoscience and remote sensing, vol. 40, no. 10, pp. 2300-2312, October 2002.
201. G. L. Bilbro, W. E. Snyder, D. E. Van den Vout, and T. K. Millarand, M. W. White, "Optimization by Mean Field Annealing, " in Advances in Neural Information Processing, D. S. Touretzky, Ed., pp. 91-98. Morgan Kaufmann, 1989.
202. G. L. Bilbro and W. E. Snyder, "Range Image Restoration Using Mean Field Annealing, " in Advances in Neural Information Processing, D. S. Touretzky, Ed., pp. 594-601. Morgan Kaufmann, 1989.
203. R. G. Wilson and S. A. Shafer, "What is the Center of the Image?, " Technical Report CMU-CS-93-122, Carnegie Mellon University, 1993.
204. R. G. Wilson, Modeling and Calibration of Automated Zoom Lenses, Ph.D. thesis, Carnegie Mellon University, January 1994.
205. A. N. Rajagopalan and S. Chaudhuri, "Performance Analysis of Maximum Likelihood Estimator for Recovery of Depth from Defocused Images and Optimal Selection of Camera Parameters, " International Journal of Computer Vision, vol. 30, no. 3, pp. 175-190, December 1998.
206. Y. Yu and Q. Cheng, "MRF Parameter Estimation by an Accelerated Method, " Pattern Recognition Letters, vol. 24, pp. 1251-1259, 2003.
207. S. Lakshamanan and H. Derin, "Simultaneous Parameter Estimation and Segmentation of Gibbs Random Fields Using Simulated Annealing, " IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 11, no. 8, pp. 799-813, August 1989.
208. S. G. Nadabar and A. K. Jain, "Parameter Estimation in MRF Line Process Models, " in Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, 1992, pp. 528-533.
209. G. Potamianos and J. Goutsias, "PARTition Function Estimation of Gibbs Random Field Images Using Monte Carlo Simulations, " IEEE Trans, on Information Theory, vol. 39, no. 4, pp. 1322-1331, July 1993.
210. G. Potamianos and J. Goutsias, "Stochastic Approximation Algorithms for PARTition Function Estimation of Gibbs Random Fields, " IEEE Trans, on Information Theory, vol. 43, no. 6, pp. 1948-1965, November 1997.
211. S. C. Zhu, Y. N. Wu, and D. Mumford, "Minimax Entropy Principle and Its Application to Texture Modeling, " Neural Computation, vol. 9, no. 8, pp. 1627-1660, 1997.
212. S. C. Zhu, Y. N. Wu, and D. Mumford, "Filters, Random Fields And Maximum Entropy, " International Journal of Computer Vision, vol. 27, no. 2, pp. 1-20, March/April 1998.
213. S. C. Zhu and X. Liu, "Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 1001-1006, July 2002.
214. P. K. Nanda, K. Sunil Kumar, S. Ghokale, and U. B. Desai, "A Multiresolution Approach to Color Image Restoration and Parameter Estimation Using Homotopy Continuation Method, " in Proc. IEEE Int. Conf. on Image Processing, Washington, D.C., USA, 1995, pp. 2045-2048.
215. R. Kashyap and R. Chellappa, "Estimation and Choice of Neighbors in Spatial-Interaction Models of Images, " IEEE trans, on Information Theory, vol. 29, no. 1, pp. 60-72, January 1983.
216. J. G. Proakis and D. G. Manolakis, Digital Signal Processing Principles, Algorithms, and Applications Prentice Hall, New Jersey, USA, 1995.
217. J. Mao and A. K. Jain, "Texture Classification and Segmentation using Multiresolution Simultaneous Autoregressive Models, " Pattern Recognition vol. 25, no. 2, pp. 173-188, 1992.
218. J. Bennett and A. Khotanzad, "Multispectral Random Field Models for Synthesis and Analysis of Color Images, " IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 20, no. 3, pp. 327-332, March 1998.