Fuzzy logic recursive motion detection and denoising of video sequences

Abstract

We propose a fuzzy logic recursive scheme for motion detection and spatiotemporal filtering that can deal with the Gaussian noise and unsteady illumination conditions in both the temporal and spatial directions. Our focus is on applications concerning tracking and denoising of image sequences. We process an input noisy sequence with fuzzy logic motion detection to determine the degree of motion confidence. The proposed motion detector combines the membership of the temporal intensity changes, appropriately using fuzzy rules, where the membership degree of motion for each pixel in a 2-D sliding window is determined by a proposed membership function. Both the fuzzy membership function and the fuzzy rules are defined in such a way that the performance of the motion detector is optimized in terms of its robustness to noise and unsteady lighting conditions. We simultaneously perform tracking and recursive adaptive temporal filtering, where the amount of filtering is inversely proportional to the confidence in the existence of motion. Finally, temporally filtered frames are further processed by a proposed spatial filter to obtain a denoised image sequence. Our main contribution is a robust novel fuzzy recursive scheme for motion detection and temporal filtering. We evaluate the proposed motion detection algorithm using two criteria: (1) robustness to noise and to changing illumination conditions and (2) motion blur in temporal recursive denoising. Additionally, we make comparisons in terms of noise reduction with other state of the art video denoising techniques.