Image analysis – Image enhancement or restoration – Artifact removal or suppression
Patent
1991-09-24
1996-06-11
Boudreau, Leo
Image analysis
Image enhancement or restoration
Artifact removal or suppression
382260, 382279, G06K 940
Patent
active
055264468
ABSTRACT:
A technique is provided to remove noise from images and to enhance their visual appearance through the utilization of a technique which converts an image into a set of coefficients in a multi-scale image decomposition process, followed by modification of each coefficient based on its value and the value of coefficients of related orientation, position, or scale, which is in turn followed by a reconstruction or synthesis process to generate the enhanced image. Also contributing to the improved enhancement is a set of orientation tuned filters of a specialized design to permit steering, with the analysis and synthesis filters also having a self-inverting characteristic. Additionally, steerable pyramid architecture is used for image enhancement for the first time, with the steering being provided by the above orientation tuned filters. The utilization of related coefficients permits coefficient modification with multipliers derived through a statistical or neural-network analysis of coefficients derived through the utilization of clean and degraded images, with the modifiers corresponding to vectors which result in translating the degraded image coefficients into clean image coefficients, in essence by cancelling those portions of a coefficient due to noise. Further improvements include an overlay of classical coring on single coefficients. Thus, the subject technique provides improved image enhancement through the use of a multi-band or scale-oriented analysis and synthesis transform having improved coefficient modification, good orientation tuning, improved bandpass characteristics, and good spatial localization.
REFERENCES:
patent: 4163258 (1979-07-01), Ebihara et al.
patent: 4523230 (1985-06-01), Carlson et al.
patent: 4549212 (1985-10-01), Bayer
patent: 4674125 (1987-06-01), Carlson et al.
William T Freeman et al "Steerable Filters for Early Vision, Image Analysis & Wavelet Decomposition" 1990 IEEE p. 406.
W. T. Freeman and E. H. Adelson. Steerable Filters for Early Vision, Image Analysis, and Wavelet Decomposition, The Media Lab, MIT, 20 Ames St., Cambridge, MA 02139, Proc. ICCV., pp. 406-415, 1990.
W. T. Freeman and E. H. Adelson. The Design and Use of Steerable Filters, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, No. 9, pp. 891-906, Sep. 1991.
E. P. Simoncelli, W. T. Freeman, E. H. Adelson and D. J. Heeger. Shiftable Multiscale Transforms, IEEE Transactions on Information Theory, vol. 38, No. 2, pp. 587-607, Mar. 1992.
T. Poggio and F. Girosi. A Theory of Networks for Approximation and Learning, MIT, Artificial Intelligence Lab. and Center for Biological Information Processing, Whitaker College, A.I. Memo No. 1140, C.B.I.P. Paper No. 31, Jul. 1989.
R. C. Gonzalez and P. Wintz. Digital Image Processing, Addison-Wesley Publishing Company, Inc., Advanced Book Program, 1977.
J. W. Woods. Subband Image Coding, Kluwer Academic Publishers, 1990.
H. J. Trussell. A Fast Algorithm for Noise Smoothing Based on a Subjective Criterion, IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-7, No. 9, pp. 677-678, Sep. 1977.
H. Knutsson and G. H. Granlund. Texture Analysis Using Two-Dimensional Quadrature Filters, IEEE Computer Society Workshop on Computer Architecture for Pattern Analysis and Image Database Management--CAPAIDM, pp. 206-213, 1983.
P. G. Powell and B. E. Bayer. A Method for the Digital Enhancement of Unsharp, Grainy Photographic Images, IEEE Int'l Conf. on Elec. Image Proc., 1982.
R. P. Lippmann. An Introduction to Computing with Neural Nets, IEEE ASSP Magazine, pp. 4-23, Apr. 1987.
S. G. Mallat. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. II, No. 7, pp. 674-693, Jul. 1989.
J-S. Lee. Digital Image Enhancement and Noise Filtering by Use of Local Statistics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-2, No. 2, pp. 165-168, Mar. 1980.
D. Clarke and M. Norman. Spyglass Dicer 2.0, Volumetric Data Analysis and Presentation for the Macintosh, National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Apr. 30, 1993.
M. Kass and A. Witkin. Analyzing Oriented Patterns, Schlumberger Palo Alto Research, 3340 Hillview Ave., Palo Alto, CA 94394, Readings in Computer Vision: Issues, Problems, Principles and Paradigns, Fischler & Firschein, eds., pp. 268-276, 1985.
E. P. Simoncelli and E. H. Adelson. Subband Transforms, J. W. Woods, Subband Image Coding, Kluwer Academic, 1991.
B. E. Bayer and P. G. Powell. A Method for the Digital Enhancement of Unsharp, Grainy Photographic Images, Advances in Computer Vision and Image Processing, vol. 2, pp. 31-88, Copyright 1986.
J-F Abramatic and L. M. Silverman. Nonlinear Restoration of Noisy Images, IEEE Transacations on Pattern Analysis and Machine Intelligence, vol. PAMI-4, No. 2, Mar. 1982.
H. E. Knutsson, R. Wilson and G. H. Granlund. Anisotropic Nonstationary Image Estimation and Its Applications: Part I--Restoration of Noisy Images, IEEE Transactions on Communications, vol. COM-31, No. 3, Mar. 1983.
P. J. Burt and E. H. Adelson. The Laplacian Pyramid as a Compact Image Code, IEEE Transactions on Communications, vol. COM-31, No. 4, Apr. 1983.
E. H. Adelson, E. Simoncelli and R. Hingorani. Visual Communications and Image Processing II, MIT, Media Lab, Cambridge, MA 02139 and SRI David Sarnoff Research Center, Princeton, NJ 08540, A Reprint from the Proceedings of SPIE--The International Society for Optical Engineering, vol. 845, Oct. 1987.
J. Lubin. Adaptive Coring Techniques or Spatio-Temporal Signals, David Sarnoff Research Center, Princeton, NJ 08543-5300, 1991.
Adelson Edward H.
Freeman William T.
Boudreau Leo
Kelley Chris
Massachusetts Institute of Technology
Tendler Robert K.
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