Video coding standard in video surveillance cameras/DVRs/NVRs

[Anonymous]

The original video file is very large, not suitable for storage and transmission. For example, according to the smallest YU(Cb)V(Cr)4:2:0 format, the SD resolution is 1280*720, and the frame rate is 25fp/s. How big is the data volume?

Each frame is 1280×720×8×(1+1/4+1/4)/8=1382400Bytes= 1350KB, about=1.318359375M, and then multiplied by 25 frames, the original data per second is 1.32M×25=33M. Think about it, this is just a video file size of 1 million pixels and 1s. If it is more high-definition, the huge amount of data will be a huge burden for our ordinary network bandwidth and storage.

Video files are compressed according to a certain method, also called encoding, which can greatly reduce the file size, which is obviously more conducive to the transmission, storage and application of video files. And this compression standard was formulated, called the video coding standard, in order to be accepted by the industry and users.

Regarding video coding standards, various companies, standardization organizations, and industry associations are involved. At present, the main organizations that formulate video coding standards are mainly these:

1. ISO/IEC MPEG. The MPEG organization recognized by ISO and IEC mainly formulates video coding standards for the MPEG series, MPEG-1, MPEG-2, MPEG-3, MPEG-4, MPEG-7 and other standards. The latest MPEG-21 is under development .
2. ITU-T. ITU-T is the telecommunications standardization department under the International Telecommunication Union. The video coding standards developed mainly include H.261, H.262, H.263, H.264, H.265, H.266, etc.
3. Google’s video standards are VP9, VP10, etc.
4. Apple’s QUICKTime.
5. China AVS, AVS2. The SAVC coding standard for security video surveillance formulated by the Chinese security industry.
6. SMPTE of the American Motion Picture Association.
7. Microsoft’s WMV.
8. Microsoft, Google, Apple and other companies have formed an alliance for open media (alliance for open media) and launched a new video coding standard AV1, AV2.

Organization Coding standard
ISO/IEC MPEG MPEG-1,MPEG-2,MPEG-4/AVC,MPEG-H Part2/HEVC
ITU-T H.261,H.262,H.263,H.264/AVC,H.265/HEVC,H.266/VVC
SMPTE VC-1,VC-2,VC-3,VC-5
AOM AV1, AV2
Google VP3,VP6,VP7,VP8,VP9,VP10
Apple QuickTime
China Standardization Association AVS,AVS2,AVS3
China Security Industry SAVC
Microsoft WMV
Video encoding compression method
Video compression usually includes two processes: encoding and decoding. Encoding is to convert the original video data into a compressed format for transmission and storage. Decoding is to convert the compressed video file back to the original video.

The key to compression is to remove redundant information in the video file. The main video coding compression methods include entropy coding, dictionary coding, and motion compensation. The detailed theory can be found in the reference material at the end of the article.

 

[Anonymous]

The pros and cons of video coding technology can be measured from two aspects: computational complexity and compression quality.

In terms of computational complexity, the lower the computational complexity of an ideal encoder, the better. In terms of compression quality, the bit rate and lossy degree of the compressed video must be considered at the same time. After compression, the lower the bit rate and the degree of loss, the better. There is a trade-off relationship between the two. The ideal encoder aims to provide the best compromise between the bit rate and the degree of loss.

Under normal circumstances, there is also a trade-off relationship between the computational complexity of the encoder and the compression quality, which depends on the application. For example, when the application is the storage of video data, a design with higher computational complexity and compression quality can be selected. When the application is a video conference or mobile phone video call, it is limited by the requirements of instant (real-time) communication or limited computing resources, and a design with lower computing complexity and compression quality may be selected.

Since the quality of the encoded video is ultimately judged by the human eye, when measuring the degree of loss, a video quality measurement standard consistent with human visual perception should be used.