Video Noise Reduction Method Using Adaptive Spatial-Temporal Filtering

Abstract

We proposed a novel method of video noise reduction based on the spatial Wiener filter and the temporal filter. In the proposed spatial Wiener filter, both the amount of noise and the size of the mask are taken into consideration. The proposed model has a great capacity to be adaptive in each area in accordance with the amount of noise. In the proposed model, the motion detector is applied to control the noise removal process in accordance with the area’s information (i.e., static or movable). More accurately, more noise removal is done in the areas that are potentially still areas and less removal in the areas that are potentially motion areas. The proposed model achieves a maximum gain of 7.6 dB and capacity of conserving the significant image features (e.g., edges). The experimental results demonstrate that the new approach is more efficient than reference methods in terms of noise removal and edges preservation.