Performance analysis of a correlation-based optical flow algorithm under noisy environments

This paper presents the performance test and analysis of a correlation-based optical flow estimation (CBOFE) algorithm, the Camus method, under various noisy environments. The noise sensitivity of the original algorithm is tested under different noise sources such as additive Gaussian, bit quantization multiplicative noises and combinations of multiplicative and additive noises. We show the efficiency of pre-filtering under different noisy environments. The SNR equations are derived for various additive and multiplicative noise cases for analyzing the performance degradation. The simulation results show that the multiplicative noise is comparable to additive noise if the standard deviations of noises are scaled to the same percentage of the full range of signal