Vision is the most important source of information for humans and video has become a part of the everyday life. Video processing is a particular case of signal processing where the input and output signals are video files or video streams. Video denoising is especially interesting for surveillance systems but als for television and medical video. Many video denoising techniques have been published in the past two decades. They vary in a wide range of complexity, performance and implementation cost. The search for efficient video denoising methods is still a valid challenge at the crossing of functional analysis and statistics. The main focus of this study is to compare various Video Denoising algorithms.
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