Code rate control method for stabilizing video quality

Abstract

The invention relates to an image transmission technology, in particular to a code rate control method for stabilizing video quality, which is realized by the following technological measures and comprises the following steps: S1: estimating the complexity of P frame type images or the complexity of I frame type images; S2: obtaining the pre-allocation code rates of k frame images; S3: calculating the quantization parameter QPk of a k frame according to the complexity of the P frame type images and the pre-allocation code rates of the k frame images or the complexity of the I frame type images and the pre-allocation code rates of the k frame images; and S4: coding and regulating the compression ratio by an encoder according to the quantization parameter QPk so as to further control the output code rate of the video. The invention can smoothly control and regulate the video quality and satisfy the video requirements of a large amount of application occasions.

Description

technical field [0001] The invention relates to image transmission technology, in particular to a code rate control method for stabilizing video quality. Background technique [0002] During data signal transmission, because the amount of video data is large and the channel bandwidth is relatively small, the video signal needs to be compressed. The purpose of video signal compression is to compress the amount of video data and realize video transmission under the condition of limited channel bandwidth. At present, PSNR (peak signal-to-noise ratio, peak signal-to-noise ratio) is generally used as an objective standard for evaluating video quality. Compared with peak signal-to-noise ratio, SSIM (structural similarity, structured similarity) can better reflect HSV (human visual system, human visual system) characteristics, and it has normalized characteristics. The bit rate control scheme related to video quality is an important research direction of video coding. There are tw...

AI Technical Summary

Problems solved by technology

In real-time video communication applications, considering the delay constraints, a single-pass (1-PASS) rate control algorithm must be used. In this case, when the scene changes or there is a large motion in the video, neither two-pass (2-pass) is allowed. -PASS) algorithm re-optimizes the bit rate distribution between video frames, and does not allow large output bit rate fluctuations, so the bit rate obtained by large motion videos is not enough to support higher video quality, which will inevitably lead to a decline in video quality ;VBR allows the bit rate to change within a certain range according to the complexity of the scene, and the change of the bit rate within a certain range is used to exchange for a relatively stable subjective video quality, but many current VBR algorithms cannot meet the requirements of smooth control and stable video quality , and the calculation is complex and difficult to implement. The VBR algorithm is divided into two types: multi-channel and single-channel. Multi-channel technology can provide better video quality, but due to its high computational complexity and non-real-time characteristics, it cannot be used in Used in real-time video communication systems, real-time video communication systems generally use single-channel VBR method

Most existing single-channel VBR algorithms use such as figure 1 In the open-loop structure shown, the algorithm focuses on how to better allocate and control the bit rate of the image layer or macroblock layer under a certain reference code rate and the fluctuation range constraints based on the reference code rate, so as to achieve the improvement of PSNR, so that Improve video quality; there is a type of single-channel VBR algorithm that does not care about the reference bit rate, but only sets a constant quantization parameter QP, but the video output bit rate obtained by this algorithm is very unstable, and is not suitable for network video, etc. Applications requiring control

Images