Video rate control method with low complexity

Abstract

The invention relates to a simple video code rate control method, which comprises bit rate preset process and quantified parameter adjustment, wherein the bit rate preset process uses video sequence character to preset the code rate; the quantified parameter adjustment uses the video sequence character to predict the code complexity, to evaluate the quantified parameters; the video sequence character is the differential diagram representing the local motion of video sequence. The invention has the advantages that: it can adjust the code rate distribution via the change to video content; the quantified parameters have simple calculation, with adaptive content; the code distribution and adjustment can match the change of video content; and it uses accumulation refresh statistic method to avoid time delay.

Description

technical field [0001] The present invention relates to a code rate control mechanism, more specifically, the present invention relates to a low-complexity video code rate control method based on original video statistical characteristics. Background technique [0002] Rate control technology is a hot issue in the field of video coding and communication, and plays a very important role in video communication. The code rate control technology can generally be divided into three types: one is to use the analytical model of the code rate-quantization parameter; The advantage of the first type of method is that bit rate adjustment can be optimized by analytical methods, but due to the randomness of the video content itself, a single analytical model cannot accurately describe the characteristics of the video itself, so more control is required The parameters can get a satisfactory effect, and the complexity is very high. The second type of method is simple to operate, but the ...

AI Technical Summary

Problems solved by technology

The advantage of the first type of method is that bit rate adjustment can be optimized by analytical methods, but due to the randomness of the video content itself, a single analytical model cannot accurately describe the characteristics of the video itself, so more control is required parameters to get a more satisfactory effect, the complexity is very high

The second type of method is simple to operate, but the control precision is not enough

Although such a model effectively combines the analytical model and the buffer control model, it can meet the requirements in terms of bit rate control accuracy, but because the video sequence itself is difficult to accurately predict (high complexity) through the analytical model, the existing The method cannot accurately control the bit rate according to the inherent rate-distortion (R-D) property of the video sequence itself, but regards the video sequence as a smooth random process to control the bit rate.

But the video sequence itself is a non-stationary random process, which will make the R-D performance of the existing bit rate control method not high

Images