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YouTube originally offered videos at only one quality level, displayed at a resolution of 320×240 pixels using the Sorenson Spark codec (a variant of H.263), [29] [30] with mono MP3 audio. [31] In June 2007, YouTube added an option to watch videos in 3GP format on mobile phones. [32]
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). Video processing systems may introduce some amount of distortion or artifacts in the video signal that negatively impact the user's perception of the system.
In a subjective quality comparison conducted in 2014 featuring the reference encoders for HEVC (HM 15.0), MPEG-4 AVC/H.264 (JM 18.6), and VP9 (libvpx 1.2.0 with preliminary VP9 support), VP9, like H.264, required about two times the bitrate to reach video quality comparable to HEVC, while with synthetic imagery VP9 was close to HEVC. [36]
For the first few years of its existence, YouTube offered only one, low-definition resolution of 256x144 or 144p at 30~50 fps or less, later extending first to widescreen 426×240, then to gradually higher resolutions; once the video service had become well established and had been acquired by Google, it had access to Google's radically ...
Users could view 4K video by selecting "Original" from the quality settings until December 2013, when the 2160p option appeared in the quality menu. [78] In November 2013, YouTube began to use the VP9 video compression standard, saying that it was more suitable for 4K than High Efficiency Video Coding (HEVC). Google, which owns YouTube ...
The quality the codec can achieve is heavily based on the compression format the codec uses. A codec is not a format, and there may be multiple codecs that implement the same compression specification – for example, MPEG-1 codecs typically do not achieve quality/size ratio comparable to codecs that implement the more modern H.264 specification.
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The lower the bit rate, the more coarsely the coefficients are represented and the more coefficients are quantized to zero. Statistically, images have more low-frequency than high-frequency content, so it is the low-frequency content that remains after quantization, which results in blurry, low-resolution blocks. In the most extreme case only ...