Experimental Efficiency Analysis in Robust models of Spatial Correlation Optical Flow Methods under Non Gaussian Noisy Contamination

Abstract

In this paper, we present a performance analysis of several robust models of spatial correlation optical flow algorithms including an original spatial correlation optical flow (SCOF), bidirectional for high reliability optical flow (BHR), gradient orientation information for robust motion estimation (GOI), and robust and high reliability based on bidirectional symmetry and median motion estimation (RHR) under the non Gaussian noise conditions. The simulated results are tested on 4 different in foreground and background movement characteristics of standard sequences (AKIYO, CONTAINER, COASTGUARD, and FOREMAN) in a degree of 0.5 sub-pixel translation. In our experiment, an original sequence (no noise), and noise contaminated sequences on Salt & Pepper Noise (SPN) at density (d) = 0.025d, and 0.005d, Speckle Noise (SN) at variance (v) = 0.05v, and 0.01v, and Poisson Noise (PN) are utilized. The experiment concentrates on Peak Signal to Noise Ratio (PSNR) as an indicator in the experimental performance analysis.