Image analysis – Image transformation or preprocessing
Reexamination Certificate
2007-10-16
2007-10-16
Kassa, Yosef (Department: 2624)
Image analysis
Image transformation or preprocessing
C382S235000, C382S243000, C382S277000, C345S644000
Reexamination Certificate
active
10772548
ABSTRACT:
A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.
REFERENCES:
patent: 5915038 (1999-06-01), Abdel-Mottaleb et al.
patent: 6466698 (2002-10-01), Creusere
patent: 6584413 (2003-06-01), Keenan et al.
patent: 6675106 (2004-01-01), Keenan et al.
patent: 6813384 (2004-11-01), Acharya et al.
patent: 7092965 (2006-08-01), Easwar
patent: 7171561 (2007-01-01), Noga
Andrew et al., “Rapid Analysis of Raman Image Data Using Two-Way Multivariate Curve Resoultion,”Applied Spectroscopy 52, 797 (1998).
Alsberg et al., “Speed Improvement of multivariate algorithms by the method of postponed basis matrix multiplication Part I. Principal component analysis,”Chemometrics Intell. Lab. Syst. 24, 31 (1994).
Kiers et al., “Relating two proposed methods for speedup of algorithms for fitting two- and three-way principal component and related multilinear models,”Chemometrics Intell. Lab. Syst. 36, 31 (1997).
Vogt et al., “Fast principal component analysis of large data sets,”Chemometrics Intell. Lab. Syst. 59, 1 (2001).
Vogt et al., “Fast principal component analysis of large data sets based on information extraction,”J. Chemometrics 16, 562 (2002).
Gallivan et al., “Impact of Hierarchical Memory Systems on Linear Algebra Algorithm Design,”Int. J. Supercomputer Applications 2, 12 (1988).
Bro et al., “A Fast Non-Negativity-Constrained Least Squares Algorithm,”J. Chemometrics 11, 393 (1997).
Wu et al., “The kernal PCA algorithms for wide data. Part I: theory and algorithms,”Chemometrics Intell. Lab Syst. 36, 165 (1997).
Kotula et al., “Automated Analysis of SEM X-Ray Spectral Images: A Powerful New Microanalysis Tool,”Microscopy and Microanalysis 9, 1 (2003).
Bro et al., “Improving the speed of multi-way algorithms: Part II: Compression,”Chemometrics Intell. Lab Syst. 42, 105 (1998).
Bieg Kevin W.
Kassa Yosef
Sandia Corporation
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