Colour video filtering based on vector order-statistics

The paper introduces a multichannel filtering approach for colour video denoising taking advantage of an order-statistic theory for vector-valued image signals. The proposed adaptive vector filter utilizes switching between an identity operation and a directional distance smoothing function based on the trimmed set of lowest ranked multichannel samples. Because the proposed method uses the same ordering scheme as the standard vector filters, the computational complexity of the new method is computationally attractive. Moreover, the method outperforms the standard vector filters especially in terms of signal-detail preservation. In this paper, we analyse a three-dimensional filter structure based on a cube filter window spawning 27 samples of three following frames. Thus, the proposed algorithm can be applied for the filtering of spatio-temporal or time-varying vector-valued image signals such as colour image sequences or colour video.