A METHOD FOR REDUCING NOISE IN RANGE DATA IMAGES BASED ON MRF THEOREM

The relevant structure of a Range data image is viewed as a piecewise smooth surface contaminated by noise.Once the surface parameters are determined,the Range data image can be reconstructed by using the parameters to get new pixel values,and consequently more noise in the Range data image can be reduced.In Range data images,almost all pixel characteristics are statistically and geometrically correlated with neighboring pixel characteristics.In this approach,the surface parameters are modeled as MRF on 2D lattices and the surface parameters determination problem is then formulated as a rule to find the posteriori mean estimation.