Superresolution and noise filtering using moving least squares

IEEE Transactions on Image Processing

Volumn 15, Issue 8, 2006, Pages 2239-2248

  Bose, N K ^a   Ahuja, Nilesh A ^a  

^a The Pennsylvania State University   (United States)

Author keywords

Hermite polynomials; Moving least squares (MLS); Superresolution

Indexed keywords

ALGORITHMS; IMAGE QUALITY; LEAST SQUARES APPROXIMATIONS; SIGNAL FILTERING AND PREDICTION; SPURIOUS SIGNAL NOISE;

HERMITE POLYNOMIALS; MOVING LEAST SQUARES (MLS); NOISE FILTERING; SUPERRESOLUTION;

IMAGE ENHANCEMENT;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; MOTION; REGRESSION ANALYSIS; SIGNAL PROCESSING; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; LEAST-SQUARES ANALYSIS; MODELS, STATISTICAL; MOTION; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 33746217164     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2006.877406     Document Type: Article

References (26)

1. S. P. Kim, N. K. Bose, and H. M. Valenzuela, "Recursive reconstruction of high-resolution image from noisy undersampled multiframes," IEEE Trans. Acoust., Speech, Signal Process., vol. 38, no. 6, pp. 1013-1027, Jun. 1990.
2. N. K. Bose, H. C. Kim, and H. M. Valenzuela, "Recursive total least squares algorithm for image reconstruction from noisy undersampled frames," Multidimen. Syst. Signal Process., vol. 4, no. 3, pp. 253-268, 1993.
3. M. Elad, "On the origin of the bilateral filter and ways to improve it," IEEE Trans. Image Process., vol. 11, no. 10, pp. 1141-1151, Oct. 2002.
4. M. B. Chappalli and N. K. Bose, "Simultaneous noise filtering and super-resolution with second-generation wavelets," IEEE Signal Process. Lett., vol. 12, no. 11, pp. 772-775, Nov. 2005.
5. A. Shnayderman, A. Gusev, and A. Eskicioglu, "A multidimensional image quality measure using singular value decomposition," in Proc. SPIE Image Quality and System Performance Conf., 2003, vol. 5294, pp. 82-92.
6. N. K. Bose and M. B. Chappalli, "A second generation wavelet framework for superresolution with noise filtering," Int. J. Imag. Sci. Technol., vol. 14, no. 2, pp. 84-89, 2004.
7. S. Lertrattanapanich and N. K. Bose, "High resolution image formation from low resolution frames using Delaunay triangulation," IEEE Trans. Image Process., vol. 11, no. 12, pp. 1427-1441, Dec. 2002.
8. M. B. Chappalli and N. K. Bose, "Enhanced Biggs-Andrews asymmetric iterative blind deconvolution," Multidimen. Syst. Signal Process. [Online]. Available: http://www.dsplab.ee.psu.edu/cgi-bin/ publication_files/MULT189-KG.pdf, to be published
9. M. Chiang and T. Boult, "Efficient image warping and super-resolution," in Proc. 3rd IEEE Workshop Applications of Computer Vision, 1996, pp. 56-61.
10. S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, "Fast and robust multiframe super resolution," IEEE Trans. Image Process., vol. 13, no. 10, pp. 1327-1344, Oct. 2004.
11. R. van den Boomgard and J. van de Weijer, L. D. Griffin and M. Lillholm, Eds., "Least squares and robust estimation of local image structure," in Scale-Space. New York: Springer, 2003, vol. 2695, Lect Notes. Comput. Sci, pp. 237-254.
12. M. Fenn and G. Steidl,, R. Klette, R. Kozera, L. Noakes, and J. Weickert, Eds., "Robust local approximation of scattered data," in Geometric Properties from Incomplete Data. New York: Springer, 2005, Comput. Imag. Vis..
13. H. Wendland, Scattered Data Approximation. Cambridge, U.K.: Cambridge University Press, 2005.
14. S. Mann and R. W. Picard, "Video orbits of the projective group a simple approach to featureless estimation of parameters," IEEE Trans. Image Process., vol. 6, no. 12, pp. 1281-1295, Dec. 1997.
15. IEEE Signal Process. Mag., vol. 20, no. 3, May 2003.
16. N. K. Bose and P. Liang, Neural Networks: Graphs and Algorithms. New York: McGraw-Hill, 1996.
17. C. Loader, Local Regression and Likelihood. New York: Springer, 1999.
18. M. Stone, "Cross-validatory choice of assessment of statistical predictions," J. Roy. Statist. Soc. B, vol. 36, pp. 111-147, 1974.
19. p," Technometrics, vol. 15, pp. 661-675, 1973.
20. J. Fan, Q. Yao, and Z. Cai, "Adpative varying-coefficient linear models," J. Roy. Statist. Soc. B, vol. 65, no. 1, pp. 57-80, 2003.
21. W. S. Cleveland and C. L. Loader, W. Haerdle and M. G. Schimek, Eds., "Smoothing by local regression: Principles and methods," in Statistical Theory and Computational Aspects of Smoothing. New York: Springer, 1996, pp. 10-49.
22. H. Wendland, "Local polynomial reproduction and moving least squares approximation," IMA J. Numer. Anal., vol. 21, no. 1, pp. 285-300, 2001.
23. W. S. Cleveland and E. H. Grosse, "Computational methods for local regression," Statist. Comput., vol. 1, pp. 47-62, 1991.
24. H. Grad, "Note on N-dimensional Hermite polynomials," Commun. Pure Appl. Math., vol. 2, pp. 325-330, 1949.
25. T. Pham, L. v. Vliet, and K. Schutte, "Robust fusion of irregularly sampled data using adaptive normalized convolution," in EURASIP J. Appl. Signal Process., 2005 [Online]. Available: http:// www.ph.tn.tudelft.nl/People/lucas/publications/2005/JoASP2005_TPLVKS.pdf
26. D. K. Hoffman, N. Nayar, O. A. Sharafeddin, and D. J. Kouri, "Analytic banded approximation for the discretized free propagator," J. Phys. Chem., vol. 95, no. 21, pp. 8299-8305, 1991.