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Aliasing noise processing of chrominance signals in video communication over the Internet

For video communication over Internet, restricted by transmission bandwidth, the video sampling rate is much lower than the Nyquist frequency decided by the features of sampled target. So, undersampling is a common case. Undersampling produces aliasing noise within sampling passband, which generates small-scale artifacts all over the image. Aliasing noise is much more severe factor than other noises in sampled imaging system which degrade the quality of image. Usually, chrominance components suffer from aliasing noises much more heavily than luminance component, because their sampling rate is a half of the one of luminance component. We propose novel sampling data processing methods and develop the algorithm derived by Zhi Kuan Chen[1]. In our sampling mechanism, we don't directly reduce the pixel density of chrominance components, instead, we construct 4 low density frames from one input high density frame. These four frames have different spatial shifts relative to original frame. We apply the algorithm to these four frames. The aliasing noises are reduced or eliminated. Effect of our aliasing noises processing methods depends on the accuracy of spatial shifts measuring. Fortunately, in our mechanism, the displacements or phase shifts can be decided precisely