Video transcoding method based on machine learning

Abstract

The invention relates to a video transcoding method based on machine learning. The video transcoding method comprises the following steps: modeling a quadtree partition mode of an encoding unit in an original video into multiple binary classifiers with different levels, then selecting an optimal feature set, finally, learning a data set composed of a characteristic vector and an optimal encoding parameter, namely introducing a machine learning method into video transcoding, and converting a parameter determining problem in video encoding into a classification problem. Therefore, a corresponding classifier can be selected according to the size of the current encoding unit, and a classification probability value is compared with a corresponding adaptive threshold to select the optimal encoding parameter for encoding. The adaptive probability threshold is adaptively adjusted for different video scenes, therefore, an optimal transcoding speed and transcoding quality can be obtained to ensure relatively small power consumption in a transcoding process, and the transcoding complexity is effectively reduced on the premise of guaranteeing the transcoding rate distortion performance.

Description

technical field [0001] The invention relates to video transcoding, in particular to a video transcoding method based on machine learning with low complexity and high accuracy. Background technique [0002] High Efficiency Video Coding (High Efficiency Video Coding) is currently the latest coding standard, and its goal is to further improve the rate-distortion performance on the basis of the existing standard H.264 / AVC, that is, to ensure the same video quality as H.264 / AVC , reducing the bit rate by about 50%. It is precisely because of this goal and ideal rate-distortion performance that more and more scholars study it. However, in real life, a code stream is often required to be used in many different devices and systems. Then, video transcoding would be a suitable solution. [0003] Video transcoding converts one video stream into another. During this process, many attributes in the code stream may change accordingly, such as frame rate, resolution, and encoding struc...

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Problems solved by technology

[0005] In the prior art, most of the statistical thresholds are used to achieve early termination in fast coding or transcoding to achieve the purpose of fast coding or fast transcoding, but these statistical thresholds are statistical experience values ​​obtained through some specific test sequence training, for Some sequences and some scenes may be effective, but not all test sequences are effective; in the existing methods, there are also fast algorithms in video encoding or video transcoding based on machine learning methods, but these methods are only The parameter determination problem in video coding is simply modeled as a classification problem. There is no effective control scheme for the accuracy of classification, that is, there is no effective balance between complexity and coding performance, and the accuracy of classification directly affects the final encoding performance

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