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Video denoising is the process of removing noise from a video signal. Video denoising methods can be divided into:
 * Spatial video denoising methods, where image noise reduction is applied to each frame individually.
 * Temporal video denoising methods, where noise between frames is reduced. Motion compensation may be used to avoid ghosting artifacts when blending together pixels from several frames.
 * Spatial-temporal video denoising methods use a combination of spatial and temporal denoising. This is often referred to as 3D denoising.

It is done in two areas:

They are chroma and luminance, chroma noise is where one see color fluctuations and luminance is where one see light/dark fluctuations. Generally, the luminance noise looks more like film grain while chroma noise looks more unnatural or digital like.

Video noise types
Video denoising methods are designed to work with many different noise factors. Typical video noise types are following:
 * Analog noise
 * Radio channel artifacts
 * High frequency interference (dots, short horizontal color lines, etc.)
 * Brightness and color channel interference (problems with antenna)
 * Video reduplication – false contouring appearance
 * VHS artifacts
 * Color-specific degradation
 * Brightness and color channel interference (specific type for VHS)
 * Chaotic line shift at the end of frame (lines resync signal misalignment)
 * Wide horizontal noise strips (old VHS or obstruction of magnetic heads)
 * Film artifacts (see also Film preservation)
 * Dust, dirt, spray
 * Scratches
 * Curling (emulsion exfoliation)
 * Fingerprints
 * Digital noise
 * Blocking – low bitrate artifacts
 * Ringing – low and medium bitrates artifact especially on animated cartoons
 * Blocks (slices) damage in case of losses in digital transmission channel or disk injury (scratches on DVD)

Different suppression methods are used to remove all these artifacts from video.

Metrics
Correct evaluation of noise reduction is required for advanced development of video denoising, improving and benchmarking existing algorithms. Standart metrics for video quality assessment, PSNR and SSIM, are often used for this purpose. In recent years, new, more advanced metrics have appeared, such as: DSI, MSDDM, FSIM, SR-SIM, MSSIM, SFF, PSNR-HVSM

Software
Most general purpose video editing software will have one or more noise-reduction functions (median, blur, despeckle, etc.).


 * VirtualDub MSU Noise Estimation Filter — this filter for open-source program MSU VirtualDu is used to estimate mean noise variance in video sequences
 * Alparysoft Denoise Filter for Adobe After Effects — this plugin for Adobe After Effects allows for mean noise estimation in video sequences
 * MSU VQMT — MSU Video Quality Measurement Tool (VQMT) is a program for objective video quality assessment. It can calculate metrics for estimating noise in video sequence
 * Adobe After Effects — a digital visual effects, motion graphics, and compositing application. It includes noise removal tools
 * Red Giant Magic Bullet — a specialized video editing tool. It includes plugin for noise removal
 * Neat Video — Neat Video is a powerful video editing plug-in designed to reduce digital noise, flicker and other imperfections
 * MSU Denoiser Filter – filter designed for noisy video stream processing, video quality improvement, or video preprocessing (e.g. for preprocessing before compression or deinterlacing)
 * Adobe Photoshop — it is a raster graphics editor. It includes instruments for noise removal
 * Movavi Video Converter Premium — a video editing software with built-in tool for noise correction