Code rate control method, device, image acquisition device and readable storage medium

Abstract

The code rate control method, device, image acquisition device, and readable storage medium provided by the embodiments of the present invention, wherein, the method obtains the gain and exposure time of the image to be encoded from the image processing module of the image acquisition device; according to the The gain and exposure time of the image to be encoded obtain the corresponding reference distortion degree; calculate the difference between the distortion degree of the characteristic area in the image to be encoded and the reference distortion degree; Calculate the difference to obtain the distortion tolerance of each macroblock in the image to be encoded; perform macroblock prediction on each macroblock in the image to be encoded to obtain the best macroblock prediction mode; The image to be encoded is encoded, so as to control the code rate of the image to be encoded. The method can achieve code rate control through the linkage of image processing and encoding, and at the same time ensure that the encoded image has a good subjective presentation.

Description

technical field [0001] The present invention relates to the monitoring field, in particular to a method, device, image acquisition device and readable storage medium for controlling the code rate of a monitoring video. Background technique [0002] Surveillance has undergone tremendous changes in recent years. Digitalization and high-definition have comprehensively improved the clarity of the image, which also puts forward higher requirements for network bandwidth. Now the mainstream 1080P has been gradually replaced by 5M, 8M or even 12M resolution, followed by The problem of insufficient bandwidth. Under the limited bandwidth, we need to work hard on video coding to achieve higher quality pictures. In the existing technology, there are schemes to control the bit rate through the complexity of image textures. For example, high-complexity textures use high-quality The above-mentioned scheme is evaluated from the objective condition of image texture complexity, and the same...

AI Technical Summary

Problems solved by technology

Under the limited bandwidth, we need to work hard on video coding to achieve higher quality pictures. In the existing technology, there are schemes to control the bit rate through the complexity of image textures. For example, high-complexity textures use high-quality The above-mentioned scheme is evaluated from the objective condition of image texture complexity, and the same bit rate control is used for image areas with the same complexity, such as grass and flower beds, ignoring the subjectivity of the human eye. I feel that although the code rate of the encoded picture is controlled, the subjective presentation of the picture is poor, and it is difficult to meet user expectations, which affects the user experience

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