Title :
Image restoration by parallel simulated annealing using compound Gauss-Markov models
Author :
Rastogi, Sanjeev ; Woods, John W.
Author_Institution :
Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
A parallel simulated annealing algorithm is presented for image restoration using a compound Gauss-Markov field model for the image. Results are provided for its implementation on a distributed array processor (DAP510) which is a single instruction multiple data (SIMD) machine with 1024(32×32) mesh-connected processor elements, and a clock rate of 10 MHz. The total time required for restoring a monochrome blurred and noisy image with continuous range of intensities is reduced to about 10 minutes as compared to 20 hours for its sequential implementation (VAX11/785). Both the maximum a posteriori (MAP) and minimum mean square error (MMSE) estimates of the original image are obtained. The parallel estimates are shown, as well as the sequential estimate and the classical Wiener filter estimate
Keywords :
Markov processes; computerised picture processing; parallel algorithms; simulated annealing; DAP510; MAP image estimate; MMSE image estimate; SIMD machine; classical Wiener filter estimate; compound Gauss-Markov field model; distributed array processor; image restoration; monochrome blurred noisy image; parallel estimates; parallel simulated annealing algorithm; sequential estimate; Additive noise; Computational modeling; Concurrent computing; Gaussian processes; Image coding; Image restoration; Integrated circuit modeling; Noise reduction; Simulated annealing; Wiener filter;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-0003-3
DOI :
10.1109/ICASSP.1991.151024
