Title :
Image restoration by complexity regularization via dynamic programming
Author :
Yau, Sze Fong ; Bresler, Yoram
Author_Institution :
Illinois Univ., Urbana, IL, USA
Abstract :
The restoration of an image modeled by piecewise-constant polygonal patches from its blurred (bandlimited) and noise corrupted version is considered. Under this model, the line-integral projections of the data image are piecewise linear signals, blurred and corrupted by noise. The break points and the associated amplitude parameters of each projection are estimated by minimizing the 1-D stochastic complexity of the projection using a recently proposed dynamic programming technique. The final image is reconstructed by convolution backprojection
Keywords :
computational complexity; dynamic programming; image reconstruction; piecewise-linear techniques; 1-D stochastic complexity; amplitude parameters; blurred image; break points; complexity regularization; convolution backprojection; dynamic programming; image restoration; line-integral projections; noisy image; piecewise linear signals; piecewise-constant polygonal patches; Amplitude estimation; Convolution; Dynamic programming; Image reconstruction; Image restoration; Magnetic resonance imaging; Piecewise linear techniques; Signal restoration; Smoothing methods; Stochastic resonance;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0532-9
DOI :
10.1109/ICASSP.1992.226240
