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What is the high compression algorithm in the surveillance camera?

There are two kinds of compression algorithms in surveillance cameras, MPEG and H.264. The former is used only under specific format requirements, but it will produce a lot of pressure on the bandwidth, while H.264 is twice as high as MPEG in compression capacity, so it can obtain a higher compression ratio. And many of the high-definition network cameras in the security industry now use H.264, so what is H.264? What are its advantages? Please read carefully the analysis instructions put together by Xuan Zhan Technology for you.

 

H.264 is built on the foundation of MPEG-4 technology, its encoding and decoding process mainly includes 5 parts: interframe and intra-frame guessing, change and reverse change, quantization and reverse quantization, loop filtering, coding. Its most valuable is undoubtedly the higher data compression ratio. Under equal picture quality conditions, the data compression ratio of H.264 is 2 to 3 times higher than that of MPEG-2 used in DVD systems, and 1.5 to 2 times higher than that of MPEG-4. Because of this, video data processed through H.264 requires less bandwidth during the network transmission process and is more economical. While MPEG-2 needs to be matched at a transfer rate of 6Mbps, H.264 only needs a transfer rate of 1Mbps to 2Mbps, and its performance and processing power are quite different.

 

Compared with previous specifications such as H.263 and MPEG-4, H.264 has the biggest advantages in the following four aspects:

 

What is the high compression algorithm in the surveillance camera? - Sony Camera Information - 1

 

1. Each video frame is converted into a block composed of pixels, so that the process of video frame encoding and processing can reach the level of the block.

 

2. For some specific blocks, the motion vector of the block is determined by one or more frames that have been encoded, and the main block is thus guessed in the subsequent encoding and decoding.

 

3. The method of spatial redundancy is selected to carry out spatial guessing, transformation, optimization and entropy coding (variable length coding) for some original blocks of video frames.

 

4. Encode the residual blocks in the video frame by using the leftover space redundancy technology. For example, regarding the difference between the source block and the corresponding guess block, transformation, optimization and entropy coding are again selected.

 

 

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