Video denoising

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.[1]

It is done in two areas:

They are chroma and luminance; chroma noise is where one sees color fluctuations, and luminance is where one sees light/dark fluctuations. Generally, the luminance noise looks more like film grain, while chroma noise looks more unnatural or digital-like.[2]

Video denoising methods are designed and tuned for specific types of noise. Typical video noise types are the 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)
  • 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.

  1. ^ Ercole, Chiara; Foi, Alessandro; Katkovnik, Vladimir; Egiazarian, Karen (20 October 2017). "Spatio-temporal pointwise adaptive denoising of video: 3D non-parametric approach". CiteSeerX 10.1.1.80.4529.
  2. ^ "Image Noise: Examples and Characteristics". www.cambridgeincolour.com.