The Institute for Telecommunications Sciences has its own VQM developed by the System Performance Standards Group. Information about this model is available on their Video Quality Research web page. It's documented in NTIA Report 02-392. This model compares a reconstructed video stream against the original by looking at luminance, gain, spatial and temporal distortions, non-linear scaling and clipping, blocking, and blurring. It is specifically applicable to television (e.g. MPEG-2) and video-conferencing streams (e.g. MPEG-4, H.263), as well as general purpose video streams.

The Sarnoff JNDmetrix VQM works differently, but at first glance appears to be less complex. It may, however, be computationally more expensive because it performs a gaussian blur and computes non-linear "busyness" values. Basically, this model looks at local distortions between the reconstructed and original images or video frames and then weights those distortions based on the busyness of the local area. The idea being that people don't notice errors in areas that are visually busy. Since this model applies to single images regardless of encoding, it is applicable to any video codec.

The third VQM, Perceptual Image Distortion, is described in a paper by Patrick C. Teo and David J. Heeger. This model passes an image through a linear filter identifying spatial and orientation characteristics. Normalized local-energy calculations are used to identify distortions in the transformed image. Since this calculation is also done only on images, it should be applicable to any video codec.

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