Self-adaptive control method for code stream of surveillance camera

Abstract

The invention discloses a self-adaptive control method for a code stream of a surveillance camera. The self-adaptive control method for the code stream of the surveillance camera comprises the steps of, after frame information of an input image is acquired through a sensor, firstly inputting the image into an image scene classifier for current scene judgment so as to obtain an experience QP value of the current scene; then enabling the image to enter an initial QP obtainer of the image frame and determining the initial QP value of the current frame image based on each frame image after the scene is determined; and finally enabling the image to enter a macro-block level QP obtainer of the image frame to obtain a macro-block level QP value and finish image coding in the end. According to the self-adaptive control method for the code stream of the surveillance camera, the surveillance camera can select the macro-block level QP value exactly based on different scenes, the fluctuation range of the code stream is reduced obviously, the quality of the code stream is improved, the code stream is reduced, the network bandwidth and the storage space are saved, the product quality is improved, and the system storage cost is decreased.

Description

technical field [0001] The invention belongs to the technical field of video monitoring, and in particular relates to an adaptive control method of a code stream of a monitoring camera. Background technique [0002] The bit stream in the video communication system has inherent variable bit rate characteristics. If the encoding parameters are kept unchanged during the encoding process, the number of bits consumed between different frames will be significantly different. Especially when the video scene is switched, there will be a sudden change in the code rate, and in the multimedia communication system with limited bandwidth, this kind of code stream with a significant change in the code rate is not suitable for network transmission and storage. [0003] The current code flow control methods include: selecting a macro block QP value (quasi-peak, quasi-peak value) to control the code rate by means of macro block level complexity calculation; or selecting a macro block QP valu...

AI Technical Summary

Problems solved by technology

These algorithms select quantization parameters by means of prediction, which has high computational complexity, cannot effectively obtain the experience value of the corresponding scene, reduces the efficiency of encoding, and the video quality drops sharply when the scene changes

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