Recognition of Degraded Images by Legendre Moment Invariants
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P. Campisi and K. Egiazarian, Blind Image Deconvolution: Theory and Applications. Boca Raton, FL: CRC, 2007.
A. Savakis and H. J. Trussell, “Blur identification by residual spectralmatching,” IEEE. Trans. Image Process. vol. 2, no. 2, pp. 141–151,Feb. 1993.
R. Molina, J. Mateos, and A. K. Katsaggelos, “Blind deconvolution using a variational approach to parameter, image, and blur estimation,” IEEE Trans. Image Process., vol. 15, no. 12, pp. 3715–3727, Dec. 2006.
M. Sorel and J. Flusser, “Space-variant restoration of images degraded by camera motion blur,” IEEE Trans. Image Process., vol. 17, no. 2, pp. 105–116, Feb. 2008.
S. W. Jung, T. H. Kim, and S. J. Ko, “A novel multiple image deblurring technique using fuzzy projection onto convex sets,” IEEE SignalProcess. Lett., vol. 16, no. 3, pp. 192–195, Mar. 2009.
J. Flusser, T. Suk, and S. Saic, “Recognition of blurred images by themethod of moments,” IEEE Trans. Image Process., vol. 5, no. 3, pp.533–538, Mar. 1996.
J. Flusser and T. Suk, “Degraded image analysis: An invariant approach,”IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 6, pp.590–603, Jun. 1998.
J. Liu and T. X. Zhang, “Recognition of the blurred image by complexmoment invariants,” Pattern Recognit. Lett., vol. 26, no. 8, pp.1128–1138, 2005.
J. Flusser, T. Suk, and S. Saic, “Recognition of images degraded by linear motion blur without restoration,” Comput. Suppl., vol. 11, pp.37–51, 1996.
A. Stern, I. Kruchakov, E. Yoavi, and S. Kopeika, “Recognition of motion-blurred images by use of the method of moments,” Appl. Opt., vol.41, no. 11, pp. 2164–2172, 2002.
J. Lu and Y. Yoshida, “Blurred image recognition based on phase invariants,” IEICE Trans. Fundam. Electron. Comm. Comput. Sci., vol.E82A, pp. 1450–1455, 1999.
X. H. Wang and R. C. Zhao, “Pattern recognition by combined invariants,”Chin. J. Electron., vol. 10, no. 4, pp. 480–483, 2001.
Y. Zhang, C. Wen, and Y. Zhang, “Estimation of motion parameters from blurred images,” Pattern Recognit. Lett., vol. 21, no. 5, pp.425–433, 2000.
Y. Zhang, C. Wen, Y. Zhang, and Y. C. Soh, “Determination of blur and affine combined invariants by normalization,” Pattern Recognit.,vol. 35, no. 1, pp. 211–221, 2002.
Y. Zhang, Y. Zhang, and C.Wen, “A new focus measure method using moments,” Image Vis. Comput., vol. 18, no. 12, pp. 959–965, Dec.2000.
J. Flusser and B. Zitova, “Combined invariants to linear filtering androtation,” Int. J. Pattern Recognit. Artif. Intell., vol. 13, no. 8, pp.1123–1136, 1999.
J. Flusser, B. Zitova, and T. Suk, I. Tammy, Ed., “Invariant-based registration of rotated and blurred images,” in Proc. IEEE Int. Geoscience and Remote Sensing Symp., Hamburg, Germany, Jun. 1999, pp. 1262–1264.
B. Zitova and J. Flusser, “Estimation of camera planar motion from defocused images,” in Proc. IEEE Int. Conf. Image Processing,Rochester, NY, Sep. 2002, vol. II, pp. 329–332.
T. Suk and J. Flusser, “Combined blur and affine moment invariants and their use in pattern recognition,” Pattern Recognit., vol. 36, no. 12,pp. 2895–2907, 2003.
J. Flusser, J. Boldys, and B. Zitova, “Moment forms invariant to rotation and blur in arbitrary number of dimensions,” IEEE Trans. Pattern
Anal. Mach. Intell., vol. 25, no. 2, pp. 234–246, Feb. 2003.
F. M. Candocia, “Moment relations and blur invariant conditions for finite-extent signals in one, two and N-dimensions,” Pattern Recognit.Lett., vol. 25, no. 4, pp. 437–447, 2004.
M. Teague, “Image analysis via the general theory of moments,” J. Opt.Soc. Amer., vol. 70, no. 8, pp. 920–930, 1980.
C. H. Teh and R. T. Chin, “On image analysis by the method of moments,”IEEE Trans. Pattern Anal. Mach. Intell., vol. 10, no. 4, pp.496–513, Apr. 1988.
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