Big data aided video transmission method based on digital-analog hybrid

Abstract

The invention relates to a big data aided video transmission method based on digital-analog hybrid. The method comprises the following steps: step 1), based on a wireless video transmission system with a maximum signal to noise ratio, specifically as follows: establishing a pseudo analog video transmission framework, based on Bayesian reasoning, obtaining a minimum mean-square error estimation of a receiving end reconstruction video signal, and acquiring best prior knowledge; step 2), transmitting a signal by a signal transmitting end of the big data aided video transmission method based on digital-analog hybrid; and step 3), reconstructing a video by a signal receiving end of the big data aided video transmission method based on digital-analog hybrid. Assuming that the transmitting end and the receiving end have the same cloud data, information which is most relevant to a transmission signal in the big data is extracted to be used for reconstructing an aided video, the best prior knowledge is extracted by maximizing the signal to noise ratio of the receiving end, and a corresponding standard is set at the transmitting end to determine whether to transmit an original video signal, so as to save a transmission bandwidth. Compared with the prior art, the invention fully uses information relevant to the transmission signal in cloud mass data, so that the visual quality of the transmitted video can be enhanced.

Description

technical field [0001] The present invention relates to a large data-assisted video transmission method based on digital-analog mixing in the field of wireless video transmission. Starting from both the signal sending end and the signal receiving end, the cloud big data is used to extract the information most relevant to the sending signal to assist the receiving end in video signal reconstruction. Improve video transmission quality. Background technique [0002] With the continuous development of the mobile Internet industry, wireless video transmission technology will surely lead the rapid development of the future video field. With the popularization of 4G, people's demand for video is soaring, and mobile video service will become one of the hottest wireless application services. It is predicted that the wireless video service will become one of the core services of the 4G network in the future, but the traditional wireless video transmission has the following defects: ...

AI Technical Summary

Problems solved by technology

Therefore, traditional mobile video transmission will result in users with good channel quality also receiving poor quality video information

[0004] 2) Low robustness

Today's mobile video transmission uses different encoding and motion compensation techniques, which will lead to high dependency between packets, so the loss of one packet will lead to information decoding errors in multiple packets

At the same time, traditional source coding converts real-time data into data bits, which destroys the data characteristics of the original video information.

Therefore, under the interference of channel noise, traditional mobile video transmission will lead to a cliff effect in the reconstructed video

[0005] 3) poor effectiveness

This form of separation of source coding and channel coding is only suitable for a single user, but for multiple mobile users with different channel qualities, this method is less effective

[0006] The unreasonable design of the existing network protocol stack is the root cause of the current lack of scalability and robustness in wireless video transmission. The source coding of the application layer compresses the video to remove redundancy, and the channel coding of the physical layer increases The form of redundant anti-interference can only achieve better performance when the channel is a unicast channel and the statistical characteristics of the channel are known at the sender

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