The performance of a digital video processing and transmission system can vary significantly and depends, amongst others, on the characteristics of the input video signal (e.g. Some authors suggest that the term “objective” is misleading, as it “implies that instrumental measurements bear objectivity, which they only do in case that they can be generalized.”[3], Objective models can be classified by the amount of information available about the original signal, the received signal, or whether there is a signal present at all:[4]. Other metrics are the kappa coefficient and the outliers ratio. a video codec) are FR-based. The viewers' opinion is recorded and averaged into the mean opinion score to evaluate the quality of each video sequence. Video quality is a characteristic of a video passed through a video transmission or processing system that describes perceived video degradation (typically, compared to the original video). This paper deals with the dynamic characteristics of a sliding, rotary type small lens actuator for high recording density disk system such as digital video disc. [4] As mentioned above, these can be used for video applications as well. Minerva M. Yeung, Boon-Lock Yeo, "Video content characterization and compaction for digital library applications," Proc. For a more efficient estimation of video quality in such cases, parametric/bitstream-based metrics have also been standardized: Few of these standards have found commercial applications, including PEVQ and VQuad-HD. However, the testing procedure may vary depending on what kind of system is tested. Classification of objective video quality models, Use of picture quality models for video quality estimation, More complex full- or reduced-reference metrics, Video Multimethod Assessment Fusion (VMAF), Laboratory for Image and Video Engineering (LIVE), "No-reference image and video quality assessment: a classification and review of recent approaches", "Toward A Practical Perceptual Video Quality Metric", "Per-Scene Adaptation: Going Beyond Bitrate", "Visual quality assessment: recent developments, coding applications and future trends", ITU-T Rec. Video art typically appears in two basic varieties: single-channel and installation. For example, a model that was developed using a particular video codec is not guaranteed to be accurate for another video codec. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); Sign in with your institutional credentials, Journal of Astronomical Telescopes, Instruments, and Systems, Journal of Micro/Nanolithography, MEMS, and MOEMS. While this method is easy to implement, it does not factor in certain kinds of degradations that develop over time, such as the moving artifacts caused by packet loss and its concealment. Also, the quality of a system can be determined offline (i.e., in a laboratory setting for developing new codecs or services), or in-service (to monitor and ensure a certain level of quality). There are a large number of supportive standards, so I’ll speak to the generalities. Digital video technology can also incorporate analytical software for intelligent video, which enables capabilities such as video search, object tracking and intrusion detection. This content is available for download via your institution's subscription. Easy and inexpensive copying. A model may also be a more complicated algorithm implemented in software or hardware. Video processing systems may introduce some amount of distortion or artifacts in the video signal that negatively impacts the user's perception of a system. To access this item, please sign in to your personal account. [10] These so-called databases are created by various research laboratories around the world. PSNR is the most widely used objective image quality metric, and the average PSNR over all frames can be considered a video quality metric. Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI. Since objective video quality models are expected to predict results given by human observers, they are developed with the aid of subjective test results. Based on the results of benchmarks by the Video Quality Experts Group (VQEG) (some in the course of the Multimedia Test Phase (2007–2008) and the HDTV Test Phase I (2009–2011)), some RR/FR metrics have been standardized in ITU-T as: The Structural Similarity (SSIM) FR image quality metric is also often used for estimating video quality. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Since the world's first video sequence was recorded and transmitted, many video processing systems have been designed. There is ongoing research into developing novel objective evaluation methods which enable prediction of the perceived quality level of the encoded video before the actual encoding is performed.[11]. Digital video systems have almost fully replaced analog ones, and quality evaluation methods have changed.

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