An adaptable k-nearest neighbors algorithm for MMSE image interpolation

IEEE Transactions on Image Processing

Volumn 18, Issue 9, 2009, Pages 1976-1987

  Ni, Karl S ^a,b   Nguyen, Truong Q ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Classification; Embedding; Interpolation; Nearest neighbor; Superresolution

Indexed keywords

CLASSIFICATION; DATA-DRIVEN; EMBEDDING; EXISTING METHOD; HIGH DIMENSIONS; IMAGE INTERPOLATION ALGORITHM; IMAGE INTERPOLATIONS; IMAGE PROPERTIES; IN-DEPTH ANALYSIS; K NEAREST NEIGHBOR ALGORITHM; K-NEAREST NEIGHBORS; LOW RESOLUTION IMAGES; MARKOV APPROXIMATION; MARKOV RANDOM FIELDS; MINIMUM MEAN SQUARED ERROR SOLUTIONS; NEAREST NEIGHBOR; NEAREST NEIGHBOR ALGORITHM; NON-PARAMETRIC; REAL-WORLD; RELEVANCE MEASURE; SINGLE PASS; SUPERRESOLUTION; TEST POINTS; TRAINING DATA;

APPROXIMATION ALGORITHMS; FUZZY CONTROL; GLOBAL OPTIMIZATION; HIDDEN MARKOV MODELS; IMAGE ACQUISITION; INTERPOLATION; MEAN SQUARE ERROR; MEMBERSHIP FUNCTIONS; OPTICAL RESOLVING POWER; PIXELS; PROBABILISTIC LOGICS; PROCESS MONITORING; RADIATION HAZARDS; TEXT PROCESSING; WINDOWS;

LEARNING ALGORITHMS;

EID: 69349097340     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2009.2023706     Document Type: Article

References (53)

1. X. Li and M. Orchard, "New edge-directed interpolation," IEEE Trans. Image Process., vol. 10, pp. 1521-1527, 2001.
2. K. Jensen and D. Anastassiou, "Subpixel edge localization and the interpolation of still images," IEEE Trans. Image Process., vol. 4, pp. 285-295, 1995.
3. V. R. Algazi, G. E. Ford, and R. Potharlanka, "Directional interpolation of images based on visual properties and rank order filtering," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 1991, vol. 4, pp. 3005-3008.
4. Z. Alkachouh and M. G. Bellanger, "Fast DCT-based spatial domain interpolation of blocks in images," IEEE Trans. Image Process., vol. 9, pp. 729-732, 2000.
5. J. I. Agbinya, "Interpolation using the discrete cosine transform," Electron. Lett., vol. 28, no. 20, 1992.
6. N. Nguyen, P. Milanfar, and G. Golub, "A computationally efficient superresolution image reconstruction algorithm," IEEE Trans. Image Process., vol. 10, pp. 573-583, 2001.
7. P. Vandewalle, S. Susstrunk, and M. Vetterli, "Superresolution images reconstructed from aliased images," in Proc. SPIE/IS&T Visual Communications and Image Processing Conf., 2003, vol. 5150, pp. 1398-1405.
8. S. Borman and R. L. Stevenson, "Simultaneous multi-frame MAP super-resolution video enhancement using spatio-temporal priors," in Proc. IEEE Int. Conf. Image Processing, Kobe, Japan, Oct. 1999, vol. 3, pp. 469-473.
9. C. B. Atkins and C. Bouman, "Classification Based Methods in Optimal Image Interpolation," Ph.D. dissertation, Purdue Univ., West Lafayette, IN, 1998.
10. W. T. Freeman, T. R. Jones, and E. C. Pasztor, "Example-based superresolution," IEEE Comput. Graph. Appl., vol. 22, no. 2, pp. 56-65, Mar./Apr. 2002.
11. H. Chang, D.-Y. Yeung, and Y. Xiong, "Super-resolution through neighbor embedding," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2004, vol. 01, pp. 275-282.
12. C. A. Dávila and B. R. Hunt, "Training of a neural network for image superresolution based on a nonlinear interpolative vector quantizer," Appl. Opt., vol. 39, pp. 3473-3485, Jul. 2000.
13. F. M. Candocia and J. C. Principe, "Super-resolution of images based on local correlations," IEEE Trans. Neural Netw., vol. 10, no. 3, pp. 372-372, Mar. 1999.
14. H. Hou and H. Andrews, "Cubic splines for image interpolation and digital filtering," IEEE Trans. Acoust., Speech, Signal Process., vol. 26, 1978.
15. M. Unser, "Splines: A perfect fit for signal and image processing," IEEE Signal Process. Mag., vol. 16, no. 6, pp. 22-38, Nov. 1999.
16. A. N. Netravali and B. G. Hasskell, Digital Pictures: Representation, Compression and Standards, 2nd ed. New York: Plenum, 1995.
17. V. Kober, M. A. Unser, and L. P. Yaroslavsky, "Spline and sinc signal interpolations in image geometrical transforms," in Proc. SPIE, vol. 2363, pp. 152-161.
18. S. Yang and K. Hong, "Bilateral interpolation filters for image size conversion," Proc. Int. Conf. Image Processing, pp. 986-989, 2005.
19. P. Tsai and T. Archarya, "Image up-sampling using discrete wavelet transform," presented at the Joint Conf. Information Services, Advances in Intelligent Systems Research, 2006.
20. G. Uytterhoeven, "Wavelets: Software and Applications," Ph.D. dissertation, Katholieke Univ. Leuven, Leuven, 1999.
21. C.-M. Kao, X. Pan, M. Anastasio, and P. La Riviere, "An interpolation method using signal recovery and discrete fourier transform," presented at the IEEE Medical Imaging Conf., 1998.
22. P. J. La Riviere and X. Pan, "Mathematical equivalence of zero-padding interpolation and circular sampling theorem interpolation with implications for direct fourier image reconstruction," presented at the SPIE Medical Imaging Conf., 1998.
23. A. Temizel and T. Vlachos, "Image resolution upscaling in the wavelet domain using directional cycle spinning," J. Electron. Imag., vol. 14, no. 4, pp. 040501-040501, 2005.
24. W. K. Carey, D. B. Chuang, and S. S. Hemami, "Regularity-preserving image interpolation," IEEE Trans. Image Process., vol. 8, no. 9, pp. 1293-1297, Sep. 1999.
25. W. K. Carey, D. B. Chuang, and S. S. Hemami, "Regularity-preserving image interpolation," in Proc. Int. Conf. Image Processing, 1997, pp. 901-908.
26. K. Ni, S. Kumar, T. Q. Nguyen, and N. Vasconcelos, "Single image superresolution based on support vector regression," presented at the Int. Conf. Acoustics, Speech, and Signal Processing, May 2006.
27. K. Ni, S. Kumar, and T. Q. Nguyen, "Learning the kernel matrix for superresolution," presented at the IEEE Conf. Multimedia Signal Processing, Aug. 2006.
28. K. Ni and T. Q. Nguyen, "Kernel resolution synthesis for superresolution," presented at the Int. Conf. Acoustics, Speech, and Signal Processing, 2007.
29. K. Ni and T. Q. Nguyen, "Color image superresolution," presented at the Int. Conf. Image Processing, Sep. 2007.
30. K. S. Ni and T. Q. Nguyen, "Image superresolution using support vector regression," IEEE Trans. Image Process., to be published.
31. C. A. Dávila and B. R. Hunt, "Training of a neural network for image superresolution based on a nonlinear interpolative vector quantizer," Appl. Opt., vol. 39, pp. 3473-3485, Jul. 2000.
32. C. Miravet and F. B. Rodriguez, "A hybrid mlp-pnn architecture for fast image superresolution," Lecture Notes Comput. Sci., vol. 2714, pp. 401-401, 2003.
33. A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the em algorithm," J. Roy. Statist. Soc., vol. 39, pp. 1-38, 1977.
34. K. Su, Q. Tian, Q. Que, N. Sebe, and J. Ma, Neighborhood Issue in Single-frame Image Superresolution. Los Alamitos, CA: IEEE Computer Society, 2005.
35. K. S. Fu, Digital Pattern Recognition, 2nd ed. New York: Springer-Verlag, 1980.
36. L. P. Devroye, L. Gyorfi, A. Krzyzak, and G. Lugosi, "On the strong universal consistency of nearest neighbor regression function estimates," Ann. Statist., vol. 22, no. 3, pp. 1371-1385, 1994.
37. L. P. Devroye and T. J. Wagner, "Distribution-free consistency results in nonparametric discrimination and regression function estimation," Ann. Statist., vol. 8, no. 2, pp. 231-239, 1980.
38. R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. New York: Wiley, 2000.
39. A. F. Atiya, "Estimating the posterior probabilities using the K-nearest neighbor rule," Neural Comput., vol. 17, no. 3, pp. 731-740, 2005.
40. T. Cover, "Estimation by the nearest neighbor rule," IEEE Trans. Inf. Theory, vol. IT-14, Jan. 1968.
41. W. S. Cleveland and S. J. Delvin, "Locally weighted regression: An approach to regression analysis by local fitting," J. Amer. Statist. Assoc., vol. 83, no. 403, pp. 596-610, 1988.
42. C. G. Atkeson, A. W. Moore, and S. Schaal, "Locally weighted learning," Artif. Intell. Rev., vol. 11, pp. 11-74, 1997.
43. G. Shakhnarovich, T. Darrell, and P. Indyk, Nearest-Neighbor Methods in Learning and Vision: Theory and Practice. Cambridge, MA: The MIT Press, 2005.
44. A. B. Lee, K. S. Pedersen, and D. Mumford, "The nonlinear statistics of high-contrast patches in natural images," Int. J. Comput. Vis., vol. 54, no. 1-3, pp. 83-103, 2003.
45. K. Shi and S.-C. Zhu, Mapping Natural Image Patches by Explicit and Implicite Manifolds, pp. 1-7, Jun. 2007.
46. J. Huang and D. Mumford, "Statistics of natural images and models," presented at the IEEE Computer Society Conf. Computer Vision and Pattern Recognition, 1999.
47. G. Carlsson, T. Ishkhanov, V. de Silva, and A. Zomorodian, "On the local behavior of spaces of natural images," Int. J. Comput. Vis. vol. 76, no. 1, pp. 1-12, Jan. 2008.
48. D. C. Burr, M. C. Morrone, and D. Spinelli, "Evidence for edge and bar detectors in human vision," Vis. Res., vol. 4, pp. 419-431, 1989.
49. J. Taguchi, K. Kido, and K. Sano, "Directional image filter respectively adjusted to edge and flat regions," Syst. Comput. Jpn. vol. 30, no. 8, pp. 72-78, 1999.
50. R. C. Gonzalez and R. E. Woods, Digital Image Processing. Boston, MA: Addison-Wesley Longman, 2001.
51. M. Li and T. Nguyen, Discontinuity-adaptive de-interlacing scheme using Markov random field model, 2006.
52. G. Shakhnarovich, "Learning Task-Specific Similarity," Ph.D. dissertation, Massachusetts Inst. Technol., Cambridge, MA, 2005.
53. K. Q. Weinberger and L. K. Saul, "Unsupervised learning of image manifolds by semidefinite programming," Int. J. Comput. Vis., vol. 70, no. 1, pp. 77-90, 2006.