Digital Image Restoration Using Posterior Distribution and Updating Pixel by Self Threshold

Digital Image Restoration Using Posterior Distribution and Updating Pixel by Self Threshold

Metropolis Hastings Markov Chain Monte Carlo (MHMCMC) algorithm has been applied to simulate digital image restoration using posterior distribution and pixels update with self threshold method. This method was implemented to Lena image degraded with 0.15 th order salt and pepper noise by the variati...

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Hauptverfasser: Adil, K., Mengko, T.L.R., Suksmono, A.B., Danudirdjo, D.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Degradation
Digital images
Image restoration
Low pass filters
MHMCMC algorithm
Monte Carlo methods
Nonlinear filters
Pixel
Posteriori Distribution
Random variables
Self Threshold
Stochastic resonance
Temperature
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Zusammenfassung:Metropolis Hastings Markov Chain Monte Carlo (MHMCMC) algorithm has been applied to simulate digital image restoration using posterior distribution and pixels update with self threshold method. This method was implemented to Lena image degraded with 0.15 th order salt and pepper noise by the variation of temperature at 1.5, 2.5 and 4.5. The result of digital image restoration in gray scale at temperature 1.5 is good image restored with Delta SNR 13.072 dB. In this simulation, the number of Markov chains (1000 chains) and iteration (800 iteration) are fixed parameter
DOI:10.1109/SICE.2006.314638