Video encoding complexity measure system
AssigneeSsimwave Inc.
InventorsKai Zeng, Kalyan Goswami, Ahmed Badr
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Abstract
Classifying video for encoding optimization may include computing a content complexity score of a video, the content complexity score indicating a measure of how detailed the video is in terms of spatial and temporal information, categorizing the video into one of a plurality of buckets according to the content complexity score, each bucket representing a category of video content having a different range of content complexity scores and being associated with a ladder specific to the range, and encoding the video according to the ladder of the one of the plurality of buckets into which the video is categorized.
Claims16
A method for classifying video for encoding optimization, comprising:
- computing a content complexity score of a video, the content complexity score indicating a measure of how detailed the video is in terms of spatial and temporal information, wherein the complexity score is a function of a human perceptual quality of experience score, such that a higher complexity score relates to a lower perceptual quality of experience and a lower complexity score relates to a higher perceptual quality of experience;
- adjusting the content complexity score to account for any difference between a target bit rate and the actual bitrate,
- categorizing the video into one of a plurality of buckets according to the content complexity score as adjusted, each bucket representing a category of video content having a different range of content complexity scores and being associated with a ladder specific to the range;
- and
- encoding the video according to the ladder of the one of the plurality of buckets into which the video is categorized.
A system for classifying video for encoding optimization, comprising:
- a processor programmed to
- identify an actual bitrate of a video encoded at a target bitrate;
- generating a BD rate curve based on a dynamic range of the video;
- compute a content complexity score of the video, the content complexity score indicating a measure of how detailed the video is in terms of spatial and temporal information;
- categorize the video into one of a plurality of buckets according to the content complexity score, each bucket representing a category of video content having a different range of content complexity scores based on the BD rate curve and being associated with a ladder specific to the range;
- and
- encode the video according to the ladder of the one of the plurality of buckets into which the video is categorized.
A non-transitory computer readable medium comprising instructions for classifying video for encoding optimization, that, when executed by a processor of a computing device, cause the computing device to perform operations including to:
- identify an actual bitrate of a video encoded at a target bitrate;
- generate a BD rate curve based on at least one of a resolution of the video, generate a BD rate curve based on codecs and encoder configurations, generate a BD rate curve based on a frame rates of the video, generate a BD rate curve based on a viewing device configured to display the video or generate a BD rate curve based on a dynamic range of the video;
- compute a content complexity score of the video, the content complexity score indicating a measure of how detailed the video is in terms of spatial and temporal information;
- categorize the video into one of a plurality of buckets according to the content complexity score, each bucket representing a category of video content having a different range of content complexity scores and based on the BD rate curve and being associated with a ladder specific to the range;
- and
- encode the video according to the ladder of the one of the plurality of buckets into which the video is categorized.
Dependencies are inferred from the claim text.