• Dr. Bobby Lukose

In this paper propose a noise removal method for reducing low and high noise in digital images. An efficient Rao-Blackwellized Particle Filter (RBPF) with MLE edge Preserving approach is used for improving the learning stage of the image structural model and guiding the particles to the most appropriate direction. It increases the efficiency of particle transitions. The proposal distribution is computed by conditionally Gaussian state space models and Rao-Blackwellized particle filtering with MLE edge Preserving. The discrete state of operation is identified using the continuous measurements corrupted by Gaussian noise. The analytical structure of the model is computed by the distribution of the continuous states. The posterior distribution can be approximated with a recursive, stochastic mixture of Gaussians. Rao-Blackwellized particle filtering is a combination of a particle filter (PF) and a bank of Kalman filters. The distribution of the discrete states is computed by using Particle Filters and the distribution of the continuous states are computed by using a bank of Kalman filters. The RBPF with MLE edge Preserving is very effective in eliminating noise when compared with particle filter. In this paper different performance metrics are evaluated for this type of noise removal technique. The metrics are Mean Square error, Root Mean square error, Peak Signal to Noise Ratio, Normalized absolute Error, and Normalized Cross Correlation, Mean Absolute Error and Signal to Noise Ratio. Experimental results prove that RBPF with MLE edge Preserving outperforms for degraded surveillance images.

Kalman filter, Particle filter, Rao-Blackwellized particle filter, Sampling Importance Resampling

"A COMPARITIVE STUDY ON REDUCTION OF LOWAND HIGH GAUSSIAN NOISE IN SURVEILLANCE IMAGES USING PARTICLE FILTERS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 10, page no.478-482, October-2018, Available :http://www.jetir.org/papers/JETIR1810852.pdf

"A COMPARITIVE STUDY ON REDUCTION OF LOWAND HIGH GAUSSIAN NOISE IN SURVEILLANCE IMAGES USING PARTICLE FILTERS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 10, page no. pp478-482, October-2018, Available at : http://www.jetir.org/papers/JETIR1810852.pdf