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Examining various denoising techniques in video processing system

In this paper we have adopted different filtering techniques for removing various noises occurred in video. The quality of video plays a key role in Video Based Information Retrieval Systems(VBIRs). Noise removal is a challenging problem in image processing as well as in video processing. The presence of noise gives an image a mottled, grainy, textured, or snowy appearance. Video images often contain noise that comes from various electronic sources. Some of the electronic components that make up a video system can be sources of electronic noise. The noise is in the form of random electrical currents often produced by thermal activity within the device. The goal of preprocessing stage is to remove the noise in video. The denoising is done to improve the quality of video frame. This paper proposes different filtering techniques for removing various noises in video. The video quality is measured using Mean Square Error, Root Mean Square Error, Peak-to-Signal Noise Ratio and Average Difference. The results were compared to identify the significant filtering technique for denoising in video applications.