论文信息 - Fast wavelet techniques for near-optimal image processing

Fast wavelet techniques for near-optimal image processing

The authors present a unified mathematical approach that allows one to formulate both linear and nonlinear algorithms in terms of minimization problems related to the so-called K-functionals of harmonic analysis. They then summarize the previously developed mathematics that analyzes the image compression and Gaussian noise removal algorithms.<<ETX>>

R. DeVore | B. Lucier | Ronald A. DeVore

[1] R. DeVore,et al. Interpolation of Besov-Spaces , 1988 .

[2] D. Mumford,et al. Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[3] G. Wahba. Spline models for observational data , 1990 .

[4] O. Rioul,et al. Wavelets and signal processing , 1991, IEEE Signal Processing Magazine.

[5] Ronald A. DeVore,et al. Data compression using wavelets: error, smoothness and quantization , 1991, [1991] Proceedings. Data Compression Conference.

[6] Ken D. Sauer,et al. Bayesian estimation of transmission tomograms using segmentation based optimization , 1992 .

[7] Ingrid Daubechies,et al. Ten Lectures on Wavelets , 1992 .

[8] R. DeVore,et al. Nonlinear Wavelet Approximation in the Space C(Rd) , 1992 .

[9] R. DeVore,et al. Compression of wavelet decompositions , 1992 .

[10] Ronald A. DeVore,et al. Image compression through wavelet transform coding , 1992, IEEE Trans. Inf. Theory.

[11] Richard L. White. High-performance compression of astronomical images , 1993 .

[12] I. Johnstone,et al. Ideal spatial adaptation by wavelet shrinkage , 1994 .

[13] A. Cohen. Ten Lectures on Wavelets, CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 61, I. Daubechies, SIAM, 1992, xix + 357 pp. , 1994 .