H264
H264 is a commonly used video coding standard. It is designed for network transmission and storage. It can efficiently compress video signals and maintain high video quality.
The H264 video coding standard adopts a frame-based coding method. Each frame of video is divided into different blocks, and each block contains compressible information. The encoding process involves many complex algorithms, including transformation, quantization, entropy encoding, etc.
The H264 coding standard has many advantages, the most notable of which are high compression ratio and high quality. H264 can achieve higher video quality with less bit rate, and can reduce transmission overhead by 20% to 50% compared with MPEG-2 bit rate. In addition, H264 also supports multiple resolution video encoding, adaptive bit rate control and other functions, which can adapt to network bandwidth and device performance.
Detailed explanation of H264 source encoder process
The H264 source encoder refers to a hardware encoder that compresses and encodes an image signal (video signal) and then outputs a bit stream. The following is the flow of the H264 source encoder:
- Preprocessing: firstly acquire the video signal, and perform preprocessing on the signal including cropping, scaling, denoising and other operations to reduce the amount of subsequent calculations.
- Inter-Frame Coding: The core of H264 coding is Inter-Frame Coding, also known as Predictive Coding. This encoding method needs to first predict the difference between the current frame (P frame) and the previous frame (I frame or P frame), and this difference is called residual. Next, operations such as transformation, quantization, and entropy coding are performed on the residual signal to obtain compressed data and output it into a code stream. The purpose of predictive coding is to reduce repetitive information by utilizing the correlation between image signals.
- Intra-frame coding: Static objects that appear in the video may be fine-tuned in the two frames before and after, which will lead to poor predictive coding. Therefore, it is also necessary to use a relatively fixed encoding method - Intra-Frame Coding (Intra-Frame Coding) to encode those methods that cannot be predicted. Intra-frame coding is very important for I-frame (key frame, Intra-Coded Frame), because there is no image reference frame of other frames in I-frame, and it needs to be completely encoded into the code stream.
- Entropy coding: After the predictive coding and intra-frame coding are completed, the quantized difference signal needs to be entropy coded in order to compress the data more effectively. Entropy coding is a lossless compression method that encodes according to the frequency distribution of the difference signal and can output a code stream.
- Output: Finally, cache and output the encoded data, and transfer it to a network or storage device for subsequent decoding.
It should be noted that the above steps are not performed linearly, and many of them can be processed in parallel to improve coding efficiency. In addition, the H264 source coder should also have more functions, such as supporting multiple resolution coding, adaptive bit rate control, noise suppression, etc., to meet the needs of different application scenarios.
H264 source encoder process code implementation
The H264 encoding process is more complicated and requires a lot of mathematical knowledge and algorithms. The following is a rough pseudocode implementation:
# 配置编码器参数
encoder = h264_encoder()
encoder.set_resolution(1920, 1080)
encoder.set_bitrate(5000000)
# 编码一帧视频
frame = load_video_frame()
yuv_frame = convert_to_yuv(frame)
encoded_frame = encoder.encode_frame(yuv_frame)
# 将编码数据写入文件或传输到网络
write_to_file(encoded_frame)
The specific implementation will involve many technical details and algorithm implementation, including:
- Transforms in the spatial and frequency domains, such as the discrete cosine transform (DCT).
- Quantization and dequantization, which compress video data by resizing the transformed coefficients of each block.
- Select and optimize entropy coding methods such as Huffman coding and context-adaptive binary arithmetic coding (CAVLC).
- Coding of predicted frames and keyframes, including prediction mode selection, motion estimation, residual coding, etc.
- Bit rate control, by controlling the bit rate of each frame to balance video quality and transmission overhead.
Therefore, if you want to implement a complete H264 encoder, you need to have a deep understanding of the above technologies, understand the encoding process, and then write code according to specific requirements. The current open source video encoding libraries x264 and openh264 can be used as reference and learning purposes. For more audio and video development technologies, please refer to "Audio and Video Beginner to Master Manual" Click to view detailed categories
Summarize
The process of the H264 source coder mainly includes five steps: preprocessing, inter-frame coding, intra-frame coding, entropy coding and output.
- Preprocessing: Preprocessing the image signal, including scaling, denoising and other operations, to reduce the amount of subsequent calculations.
- Inter-frame coding: The image signal is compressed by predicting the difference (residual) between the current frame and the previous frame. Perform operations such as transformation, quantization, and entropy coding on the residual signal to obtain compressed data and output it into a code stream.
- Intra-frame coding: For signals that cannot be coded in a predictive manner, intra-frame coding is used for compression coding.
- Entropy coding: entropy coding the quantized difference signal to compress data more effectively.
- Output: Cache and output the encoded data, and transmit it to a network or storage device for subsequent decoding.
The H264 source encoder has the advantages of high compression rate and high quality, and supports multiple resolution video encoding, adaptive bit rate control and other functions to meet the needs of different application scenarios. If you want to implement a complete H264 encoder, you need to have a deep understanding of related technologies, understand the encoding process, and perform algorithm implementation and optimization.