User manual TEKTRONIX PQA600 DATASHEET

[. . . ] This test methodology can be extremely expensive to complete, and often the results are not repeatable. Thus, subjective DMOS testing with human viewers is impractical for the CODEC design phase, and inefficient for ongoing operational quality evaluation. The PQA600 provides a fast, practical, repeatable, and objective measurement alternative to subjective DMOS evaluation of picture quality. Data Sheet User Interface of PQA600. Showing reference, test sequences, with difference map and statistical graph. Picture Quality Analysis System System Evaluation The PQA600 can be used for installation, verification, and troubleshooting of each block of the video system because it is video technology agnostic: any visible differences between video input and output from processing components in the system chain can be quantified and assessed for video quality degradation. [. . . ] Another measurement is then made by the PQA600, this time using the Predicted DMOS algorithm and the resultant Perceptual Difference Map for DMOS (H) image is shown. Whiter regions in this Perceptual Contrast Difference map indicate greater perceptual contrast differences between the reference and test images. In creating the Perceptual Contrast Difference map, the PQA600 uses a human vision system model to determine the differences a viewer would perceive when watching the video. The Predicted DMOS measurement uses the Perceptual Contrast Difference Map (H) to measure picture quality. This DMOS measurement would correctly recognize the viewers perceive the jogger as less degraded than the trees in the background. The PSNR measurement uses the difference map (G) and would incorrectly include differences that viewers do not see. 4 www. tektronix. com Picture Quality Analysis System -- PQA600 Attention Map Example: The jogger is highlighted Attention Model The PQA600 also incorporates an Attention Model that predicts focus of attention. This model considers: Motion of Objects Skin Coloration (to identify people) Location Contrast Shape Size Viewer Distraction due to Noticeable Quality Artifacts These attention parameters can be customized to give greater or less importance to each characteristic. This allows each measurement using an attention model to be user-configurable. The model is especially useful to evaluate the video process tuned to the specific application. For example, if the content is sports programming, the viewer is expected to have higher attention in limited regional areas of the scene. Highlighted areas within the attention image map will show the areas of the image drawing the eye's attention. Artifact Detection Settings For example, artifact detection can help answer questions such as: "Will the DMOS be improved with more de-blocking filtering?" or, "Should less prefiltering be used?" If edge-blocking weighted DMOS is much greater than blurring-weighted DMOS, the edge-blocking is the dominant artifact, and perhaps more de-blocking filtering should be considered. In some applications, it may be known that added edges, such as ringing and mosquito noise, are more objectionable than the other artifacts. These weightings can be customized by the user and configured for the application to reflect this viewer preference, thus improving DMOS prediction. Likewise, PSNR can be measured with these artifact weightings to determine how much of the error contributing to the PSNR measurement comes from each artifact. The Attention Model and Artifact Detection can also be used in conjunction with any combination of picture quality measurements. This allows, for example, evaluation of how much of a particular noticeable artifact will be seen where a viewer is most likely to look. Artifact Detection Artifact Detection reports a variety of different changes to the edges of the image: Loss of Edges or Blurring Addition of Edges or Ringing/Mosquito Noise Rotation of Edges to Vertical and Horizontal or Edge Blockiness Loss of Edges within an Image Block or DC Blockiness They work as weighting parameters for subjective and objective measurements with any combination. The results of these different measurement combinations can help to improve picture quality through the system. www. tektronix. com 5 Data Sheet Edit Measure Dialog Configure Measure Dialog Comprehensive Picture Quality Analysis The PQA600 provides Full Reference (FR) picture quality measurements that compare the luminance signal of reference and test videos. It also offers some No Reference (NR) measurements on the luminance signal of the test video only. Reduced Reference (RR) measurements can be made manually from differences in No Reference measurements. In Summary display, the user can see the multiple measurement graphs with a barchart along with the reference video, test video, and difference map during video playback. Summary measures of standard parameters and perceptual summation metrics for each frame and overall video sequence are provided. In Six-tiled display, the user can display the 2 measurement results side by side. [. . . ] A monitor is to be provided by the user. Display Technology: CRT/LCD/DMD each with preset and user-configurable parameters (Interlace/Progressive, Gamma, Response Time, etc). Reference Display and Test Display can be set independently View Model Viewing distance, Ambient Luminance for Reference and Test independently, image cropping and registration: automatic or manual control of image cropping and test image contrast (ac gain), brightness (dc offset), horizontal and vertical scale and shift PSNR No configurable parameters Perceptual Difference The viewer characteristics (acuity, sensitivity to changes in average brightness, response speed to the moving object, sensitivity to photosensitive epilepsy triggers, etc) Attention Model Overall attention weighting for measures, Temporal (Motion), Spatial (Center, People (Skin), Foreground, Contrast, Color, Shape, Size), Distractions (Differences) Artifact Detect Added Edges (Blurring), Removed Edges (Ringing/Mosquito Noise), Rotated Edges (Edge Blockiness), and DC Blockiness (Removed detail within a block) Summary Node Measurement Units (Subjective: Predicted DMOS, PQR or % Perceptual Contrast. Objective: Mean Abs LSB, dB). , Map type: Signed on gray or unsigned on black. Worst-case Training Sequence for ITU-R BT. 500 Training (Default or User-application Tuned: Determined by Worst Case Video % Perceptual Contrast), Error Log Threshold, Save Mode Display Model Dual Link DVI port or Display port Up to 2560×1600 resolution Standard Accessories Order Number Description PQA600 Picture Quality Analysis System Documentation 071-2775-xx (English) 071-2781-xx 071-2778-xx 077-0487-xx 077-0486-xx 063-3428-xx Other Quick Start User Manual in English, and Simplified Chinese or Japanese translation if a language option was ordered Release Notes User Technical Reference Specification and Performance Verification Manual in PDF format on Documentation CD PQA600 Declassification and Security Instructions in PDF format on Documentation CD Documentation CD, containing PDF files of the documentation set Application Recovery Disk Video Sequences Recovery Media Computer System and Peripherals Component Description 020-3054-xx 020-3053-xx Operating System CPU Hard Disk Drive CD/DVD Drive Windows 7 Professional 64-bit Six-core Intel® Xeon® 5650 Series processors 5x 3. 5 in. 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