AI video cloud vs narrowband HD, who is the darling of the video era

With the gradual improvement of network technology , All kinds of video messages have become the main means of media communication . But in fact, it is not only network technology that supports video transmission , And video transcoding and compression technology . This kind of technology is divided into many , For example, it has been frequently mentioned H.265, For example, the popular narrowband HD , For example, it is inseparable from the meta universe AI Video cloud , What's the difference between them , What should we choose when choosing ？

Narrowband HD

What we usually call narrowband HD , It refers to the premise that the video coding rate remains unchanged , Methods to reduce the average video size . Take cloud narrowband HD as an example , The general workflow is to input a video transcoding fragment first , Then the complexity analysis , Then the transcoding parameters are divided into scenes , For example, slow or intense exercise , Of course, there will be a rate control algorithm to adjust the output of the encoder , Finally get the encoded video .

The complexity , Another cloud shot draws on the standard BT1788 About space perception information and time perception information in . Spatial perception information is to make one image for each frame Sobel value , Then analyze its texture as a reference standard ; Time aware information is the standard deviation of the frame difference between frames , As a change in time . At first, according to the different application scenarios of users, there are four types of scenarios ： Cell phone selfie 、 Animation 、 Slow and vigorous exercise . No user action is required , The system automatically selects the above four most appropriate methods according to the complexity analysis .

The encoder uses H.264 and H.265 Two kinds of . among H.265 It's in the video coding standard H.264 On the basis of , Further improve the compression efficiency 、 Improve robustness （Robustness Transformation resistance ） And error resilience 、 Reduce real-time delay 、 Reduce channel acquisition time and random access delay 、 Reduce complexity , To achieve optimal settings .

In narrowband HD, the two coding frameworks are similar , It's all about redundant compression in space domain and time domain . among H.264 The framework flow includes inter frame 、 Intra prediction 、 Transformation 、 quantitative 、 Inverse transform inverse quantization 、 Entropy coding and deblocking filtering . and H.265 Roughly the same as H.264 identical , Including inter frame 、 Intra prediction 、 Entropy coding, etc , It's just Deblocking To get rid of “ Block effect ", Added a new SAO Filtering to eliminate ringing effect . But although the framework is the same ,H.265 It has been technically optimized ：

• H.264 The size of the block is from 16x16 Extended to H.265 Of 64x64, This is an exponential increase in the complexity of blocks ;

• H.265 The intra prediction direction is improved to 35 Kind of . because H.265 It's for HD , Include 1080P、2K、4K, Up to 8K, The size of this kind of picture will be larger , So it can be divided into large pieces , For those large image areas where the change is not obvious , You can use a larger block size , It can reduce the complex calculation caused by blocking in the prediction link . The motion vector is also optimized , And the algorithm of brightness and chroma difference becomes more complex ;

• Added parallel computing , Because the complexity has increased a lot , And at present, the parallel technology in the computer industry is also developing very well , Therefore, parallel optimization is added when the video coding standard is formulated , To save coding time .

These optimization functions can be adjusted by setting parameters .

AI Video cloud

AI The addition of Technology , Let users know the content of the video 、 retrieval 、 Personalized recommendation 、 And so on, there are greater choices and convenience in personalized settings .

AI Video cloud through the combination of new computing power ecology 、 Edge computing and low power consumption AI Cutting edge technologies such as video chips , from AI Carry out the rapid extraction and construction of effective information , Thus reducing manpower 、 material resources 、 The loss of time .

Edge computing makes the computing power of services closer to that of users , Its basic idea is to process data 、 Running the application , Even the implementation of some functional services , From the central server to the nodes on the edge of the network , Thus, the delay of the computing system can be effectively reduced , Reduce data transmission bandwidth , Ease the pressure of Cloud Computing Center , Improve availability , Protect data security and privacy .

Different from the narrowband HD mentioned above ,AI Video cloud is more committed to building a full life cycle , Cloud edge integrated video service . Generally, we will provide services from the following aspects ：

• Quickly produce video ： Provide video recording 、 edit 、 Play as one content production solution .

• Perfectly compatible with different formats 、 Time data ： For the data storage requirements in the context of big data and Internet of things , Provide unstructured data cloud storage USS、 Integrate object storage services such as cloud storage . At the same time, it provides rapid migration services , Avoid users being trapped by data , Help users master data sovereignty .

• Intelligent analysis of massive data ： Based on new computing power ecology 、 Edge computing and low power consumption AI Cutting edge technologies such as video chips , Yes AI The algorithm is continuously trained , Give Way AI Form the ability of video understanding and video structured analysis of specific scenes . Effectively and quickly extract valuable structural information , Eliminate a lot of manpower 、 Loss of material resources and time

• cost reduction , Improve efficiency ： For multimedia data , Can effectively reduce 40-70% Video size , At the same time, it provides a variety of cutting-edge technologies such as intelligent video restoration . Let users no longer need self built services and functions , On demand on demand , Greatly reduce development costs .

• Avoid operator differences , Complete quick distribution ： Relying on a large number of node segments of cloud service providers , Cover all operators , It also provides intelligent scheduling and edge caching . It can quickly distribute application content , Improve website response speed .

that AI What's the difference between video cloud and narrowband HD ？

Compared with narrowband HD ,AI The use of video cloud is more convenient , It can also fit the user's scene better . Depending on AI Intelligent features of ,AI The video cloud will continue to adjust automatically , There will be no problem of upgrading .

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