Image clean-up and pre-coding

Image analysis – Image enhancement or restoration – Image filter

Reexamination Certificate

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C348S606000

Reexamination Certificate

active

07570832

ABSTRACT:
A method of filtering a digital image is described. A filter kernel is applied to a respective pixel in a set of pixels to smooth noise and preserve spatial frequencies associated with image edges in the digital image in accordance with a first filtering parameter. The filter kernel is a function of the respective pixel and has a closed form for the respective pixel. The filter kernel includes contributions from a first set of neighboring pixels and has a content-dependent normalization such that a sum of elements in the filter kernel equals a substantially fixed value.

REFERENCES:
patent: 5819035 (1998-10-01), Devaney et al.
patent: 6731821 (2004-05-01), Maurer et al.
patent: 7352911 (2008-04-01), Maurer
Perona, Pietro & Malik, Jitendra; Scale-Space and Edge Detection Using Anisotropic Diffusion, Jul. 1990, IEEE, IEEE Transations on Pattern Analysis and Machine Intelligence vol. 12, No. 7, 629-639.
Alvarez, L., et al., “Axioms and Fundamental Equations of Image Processing,” Arch. Rational Mech. Anal., vol. 123 (1993), pp. 199-254.
Alvarez, L., et al., “Signal and Image Restoration Using Shock Filters and Anisotropic Diffusion,” SIAM J. Numer. Anal., vol. 31, No. 2 (1994), pp. 590-605.
Alvarez, L., et al., “Image Selective Smoothing and Edge Detection by Nonlinear Diffusion, II,” SIAM J. Numer. Anal., vol. 29, No. 3 (1992), pp. 845-866.
Black, M., et al., “Robust Anisotropic Diffusion,” IEEE Trans. on Image Processing, vol. 7, No. 3 (1998), pp. 421-432.
Catte, F., et al., “Image Selective Smoothing and Edge Detection by Nonlinear Diffusion,” SIAM J. Numer. Anal., vol. 29, No. 1 (1992), pp. 182-193.
Chan, T.F., et al., “On the Convergence of the Lagged Diffusivity Fixed Point Method in Total Variation Image Restoration,” SIAM J. Numer. Anal., vol. 36, No. 2 (1999), pp. 354-367.
Chan, T.F., et al., “The Digital TV Filer and Nonlinear Denoising,” IEEE Trans. on Image Processing, vol. 10, No. 2, (2001), pp. 231-241.
Demoulini, S., “Variational Methods for Young Measure Solutions of Nonlinear Parabolic Evolutions of Forward-Backward Type and of High Spatial Order,” Appl. Anal., vol. 63 (1996), pp. 363-373.
Demoulini, S., “Young Measure Solutions for a Nonlinear Parabolic Equation of Forward-Backward Type,” SIAM J. Math. Anal., vol. 27, No. 2 (1996); pp. 376-403.
German, S., et al., “Stochastic Relaxation, Gibbs, Distributions, and the Bayesian Restoration of Images,” IEEE Trans. Pattern Anal. and Machine Intell., vol. 6 (1984), pp. 721-741.
Hollig, K., “Existence of Infinitely Many Solutions for a Forward Backward Heat Equation,” Trans. Amer. Math. Soc., vol. 278, No. 1 (1983), pp. 299-316.
Horstmann, D., et al., “Aggregation Under Local Reinforcement: From Lattice to Continuum,” Euro J. of Appl. Math., vol. 15 (2004), pp. 545-576.
Kawohl, B., et al., “Maximum and Comparison Principle for One-Dimensional Anisotropic Diffusion,” Math. Ann., vol. 311 (1998), pp. 107-123.
Kichenassamy, S., “The Perona-Malik Paradox,” SIAM J. Appl. Math., vol. 57, No. 5 (1997), pp. 1328-1342.
Kinderlehrer, D., et al., “Weak Convergence of Integrands and the Young Measure Representation,” SIAM J., Math. Anal., vol. 23, No. 1 (1992), pp. 1-19.
Mumford, D., et al., “Optimal Approximations by Piecewise Smooth Functions and Associated Variational Problems,” Comm. Pure & Appl. Math., vol. 42 (1989), pp. 577-685.
Perona, P., et al., “Scale-Space and Edge Detection Using Anisotropic Diffusion,” IEEE Trans. on Pattern Anal. and Machine Intell., vol. 12, No. 7 (1990, pp. 629-639.
Rudin, L.I., et al., “Nonlinear Total Variation Based Noise Removal Algorithms,” Physica D., vol. 60 (1992), pp. 259-268.
Sapiro, G., et al., “Anisotropic Diffusion of Multivalued Images with Applications to Color Filtering,” IEEE Trans. on Image Processing, vol. 5, No. 11 (1996), pp. 1582-1586.
Taheri, S., et al., “Young Measure Solutions and Instability of the One-Dimensional Perona-Malik Equation,” J. Math. Anal. and Appl., vol. 308 (Feb. 23, 2005), pp. 467-490.
Tang, B., et al., “Color Image Enhancement Via Chronaticity Diffusion,” IEEE Trans. on Image Processing, vol. 10, No. 5 (2001), pp. 701-707.
Torkamani-Azar, F., et al., “Image Recovery Using the Anisotropic Diffusion Equation,” IEEE Trans. on Image Processing, vol. 5, No. 11 (1996), pp. 1573-1578.
Whitaker, R.T., et al., “A Multi-Scale Approach to Nonuniform Diffusion,” CVGIP: Image Understanding, vol. 57, No. 1 (1993), pp. 99-110.
Jingxue, Y., et al., “Young Measure Solutions for a Class of Forward-Backward Diffusion Equations,” J. Math. Anal. Appl., vol. 279 (2003).
Search Report for International Application No. PCT/US2005/21099, mailed Aug. 31, 2006.
Liu, C., et al., Robust Coding Schemes for Indexing and Retrieval from Large Face Databases, IEEE, 1057-7149, 2000, pp. 132-137.
Osuna, E., et al., “Training Support Vector Machines: an Application to Face Detection,” IEEE, 1063-6919, 1997, pp. 130-136.

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