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Video Quality Metric (VQM) Software

Input Scene Dependencies Digital Transmission System Dependencies The Need for Technology Independence New Digital Video Impairments http://www.its.bldrdoc.gov/n3/video/index.html. Video Quality Metric (VQM) Software. Repeatable Video Quality Testing. Subjective Video Quality Testing.

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Video Quality Metric (VQM) Software

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  1. Input Scene Dependencies Digital Transmission System Dependencies The Need for Technology Independence New Digital Video Impairments http://www.its.bldrdoc.gov/n3/video/index.html Video Quality Metric (VQM) Software

  2. Repeatable Video Quality Testing Subjective Video Quality Testing Objective Video Quality Testing

  3. Examples of Digital Video Impairments Original Image Blurring Tiling Edge Noise

  4. ANSI T1.801.03-1996 Video Quality Parameters • Distortions are quantified using spatial and temporal gradients, or slopes, of the input and output video sequences. • The operating characteristics of digital transmission systems (e.g., bit-rate, error rate, dropped packet rate) may change over time and this can produce quality fluctuations. • Digital video systems produce fundamentally different kinds of impairments than analog video systems. Examples of these include tiling, error blocks, smearing, jerkiness, edge busyness, and object retention. • Blurring: A global distortion over the entire image, characterized by reduced sharpness of edges and spatial detail. • Block Distortion/Tiling: Distortion of the image characterized by the appearance of an underlying block encoding structure. • Error Blocks: A form of block distortion where one or more blocks in the image bear no resemblance to the current or previous scene and often contrast greatly with adjacent blocks. • Error blocks become more noticeable in low motion scenes than high motion scenes. • Noise: An uncontrolled or unpredicted pattern of intensity fluctuations that is unwanted and does not contribute to the desired quality of a video image. • Jerkiness: Motion that was originally smooth and continuous is perceived as a series of distinct snapshots.

  5. Hv_loss

  6. Si_loss

  7. Hv_gain

  8. Chroma_spread

  9. View processed data

  10. Si_gain

  11. Intermediate video

  12. Ct_spread_gain

  13. Detailed report

  14. IVQM • The IVQM tool performs automated video capture and processing of live video signals using two PCs (a source PC and a destination PC) and an IP connection. • Reduced reference features are communicated via the IP connection and used to perform destination video calibration and quality estimation. Stephen Wolf, (303) 497-3771, swolf@its.bldrdoc.gov

  15. In-Service VQM (IVQM) tool

  16. iVQM • ANSI T1.801.03 and ITU-T J.143 • This standard specifies a framework for measuring end-to-end performance parameters that are sensitive to distortions introduced by the coder, the digital channel, or the decoder as shown in the figure. • Features are quantities of information that are associated with individual video frames. • Parameters are calculated using comparison functions that operate on two parallel sequences of these feature samples (one sequence from the output video frames and a corresponding sequence from the input video frames). • Objective video quality estimation software, written in C++, processes video signals in accordance with American National Standards Institute (ANSI) T1.801.03-1996 and other more recently developed metrics, resulting in estimates of video quality that show good correlation with subjective test results.

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