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The measurement paradigm is to assess degradations of a decoded video sequence output from the network (for example as received by a TV set top box) in comparison to the original reference picture (broadcast from the studio). Consequently, the setup is referred to as end-to-end (E2E) quality testing.
291:) and analyzes the picture pixel-by-pixel after a temporal alignment (also referred to as 'temporal registration') of corresponding frames of reference and test signal. PEVQ MOS results range from 1 (bad) to 5 (excellent) and indicate the perceived quality of the decoded sequence.
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The measurement algorithm can be applied to analyze visible artifacts caused by a digital video encoding/decoding (or transcoding) process, radio- or IP-based transmission networks and end-user devices. Application scenarios address
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The development for picture quality analysis algorithms available today started with still image models which were later enhanced to also cover motion pictures. PEVQ is full-reference algorithm (see the classification of models in
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PEVQ is based on modeling the behavior of the human visual system. In addition to an overall MOS score, PEVQ quantifies abnormalities in the video signal by a variety of
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PEVQ Paper MMSP 2007, IEEE 9th
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external links, and converting useful links where appropriate into
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is an end-to-end (E2E) measurement algorithm to score the
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