Paper
2 June 2000 Detectability and annoyance value of MPEG-2 artifacts inserted in uncompressed video sequences
Michael Scott Moore, John M. Foley, Sanjit K. Mitra
Author Affiliations +
Proceedings Volume 3959, Human Vision and Electronic Imaging V; (2000) https://doi.org/10.1117/12.387146
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
Many approaches have been proposed recently for estimating the perceived fidelity of digitally compressed and reconstructed video clips. Several metrics rely on the accurate estimation of detection thresholds, basically assuming that perceived quality depends significantly on the error threshold. To test that assumption, we designed an experiment to measure the actual detection threshold of some MPEG-2 artifacts in typical video sequences. In each of the test clips, we briefly replaced a region with a test stimulus created using an MPEG-2 encoder. The location, time, and strength of the artifact were varied between test videos. At the end of each clip, each subject provided a detection response and, for the detected artifacts, location and annoyance information. From the data, we determined the detection threshold for each artifact. Using the thresholds, we computed a perceptually weighted error metric. In this paper, we describe the experiment in more detail, summarize the experimental results including the threshold calculations, and compare the weighted error measure to the output of a commercial fidelity metric. Finally, we discuss our conclusions on the validity of predicting quality from threshold measurements.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Scott Moore, John M. Foley, and Sanjit K. Mitra "Detectability and annoyance value of MPEG-2 artifacts inserted in uncompressed video sequences", Proc. SPIE 3959, Human Vision and Electronic Imaging V, (2 June 2000); https://doi.org/10.1117/12.387146
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Cited by 13 scholarly publications.
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KEYWORDS
Video

Video compression

Error analysis

Image compression

Quality measurement

Contrast sensitivity

Image processing algorithms and systems

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