We propose a three-dimensional Gaussian denoising scheme for application to color video frames. The time is selected as a third dimension. The algorithm is developed using fuzzy rules and directional techniques. A fuzzy parameter is used for characterization of the difference among pixels, based on gradients and angle of deviations, as well as for motion detection and noise estimation. By using only two frames of a video sequence, it is possible to efficiently decrease Gaussian noise. This filter uses a noise estimator that is spatio-temporally adapted in a local manner, in a novel way using techniques mentioned herein, and proposing a fuzzy methodology that enhances capabilities in noise suppression when compared to other methods employed. We provide simulation results that show the effectiveness of the novel color video denoising algorithm.

Abstract: Bioelectric signals are distorted by unwanted electric noise interference. This paper focuses on techniques that can be applied to surface electromyographic systems design to improve the signal-to-noise ratio. Three case studies are presented in this manuscript : Effects of the front-end instrumentation amplifier gain, use of dc-dc converters for single-supply operation, and dedicated hardware for 60 Hz power line noise rejection. Results show that the quality of the signal is highly improved when the suggested techniques are applied.