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 choice for media communication. But in fact, it is not only network technology that supports video dissemination, but also video transcoding and compression technology. Such technologies are divided into many categories, such as H.265, which has been frequently mentioned, such as the popular narrow-band high-definition, such as AI video cloud, which is inseparable from the Metaverse. What are the differences between them, and what should we choose when choosing?

Narrowband HD

What we usually call narrow-band HD refers to the method of reducing the video size on average under the premise that the video encoding rate remains unchanged. Taking Youpaiyun Narrowband HD as an example, the general workflow is to first input a video transcoding segment, then perform complexity analysis, and then sub-scene transcoding parameters, such as slow or violent motion, of course, there will be codes in it. Rate control algorithm to adjust the output of the encoder, and finally get the encoded video.

The complexity of this, and Paiyun draws on the spatial perception information and time perception information in the standard BT1788. Spatial perception information is to make a Sobel value for each frame of image, and then analyze its texture as a reference standard; temporal perception information is to use the standard deviation of the frame difference between frames as a temporal change. Youpaiyun initially divided into four types of scenarios according to the user's application scenarios: mobile phone selfie, animation, slow motion and violent motion. No user operation is required, and the system automatically selects the above four most suitable methods according to the complexity analysis.

The encoder uses both H.264 and H.265. Among them, H.265 is based on the video coding standard H.264, which further improves compression efficiency, improves robustness (Robustness resistance to transformation) and error recovery capability, reduces real-time delay, and reduces channel acquisition time and random access time. Extend and reduce complexity to achieve optimal settings.

In narrowband HD, the coding framework of the two is similar, and both are about redundant compression in the spatial and temporal domains. The frame process of H.264 includes prediction, transformation, quantization, inverse transform and inverse quantization, entropy coding and deblocking filtering between frames and frames. H.265 is roughly the same as H.264, including inter-frame, intra-frame prediction, entropy coding, etc., but Deblocking adds a new SAO filter to eliminate ringing effects in order to remove the "block effect". However, although the framework is the same, H.265 is technically optimized:

• The size of the H.264 block is extended from 16x16 to 64x64 of H.265, which is an exponential increase in the complexity of the block;
• The number of prediction directions within H.265 frames has been increased to 35. Because H.265 is for high-definition, including 1080P, 2K, 4K, up to 8K, the size of this kind of picture will be relatively large, so it can be divided into large blocks, for those large image areas that do not change significantly, you can use more A large block size can reduce the complex calculation caused by the block in the prediction link. The motion vector has also been optimized, and the luminance and chrominance difference algorithms have become more complex;
• Parallel computing is added, because the complexity has increased a lot, and the parallel technology in the computer industry is developing very well, so parallel optimization was added when the video coding standard was formulated to save coding time.

These optimization functions can be adjusted by setting parameters.

AI Video Cloud

The addition of AI technology allows users to have greater choices and convenience in video content, retrieval, personalized recommendations, and other personalized settings.

The AI video cloud combines cutting-edge technologies such as new computing power ecology, edge computing, and low-power AI video chips to quickly extract and construct effective information by AI, thereby reducing the loss of manpower, material resources, and time.

Among them, edge computing makes the computing power of the service closer to the user. Its basic idea is to transfer the processing of data, the operation of applications, and even the realization of some functional services from the central server to the nodes on the edge of the network, thereby effectively reducing The delay of small computing systems reduces data transmission bandwidth, relieves pressure on cloud computing centers, improves availability, and protects data security and privacy.

Different from the narrowband HD mentioned above, AI Video Cloud is more committed to creating a full-lifecycle, cloud-side integrated video service. Services are generally provided in the following aspects:

• Quickly produce video: Provide video recording, editing, and playback as one of the content production solutions.
• Perfectly compatible with data in different formats and times: for data storage requirements in the context of big data and the Internet of Things, it provides object storage services such as unstructured data cloud storage USS and converged cloud storage. At the same time, it provides fast migration services to avoid users being trapped by data and help users master data sovereignty.
• Intelligent analysis of massive data: Based on cutting-edge technologies such as new computing power ecology, edge computing, and low-power AI video chips, AI algorithms are continuously trained to enable AI to develop video understanding capabilities and video structural analysis capabilities for specific scenarios. Effectively and quickly extract valuable structural information, avoiding the loss of a lot of manpower, material resources and time
• Reduce costs and improve efficiency: For multimedia data, it can effectively reduce video size by 40-70%, and provide various cutting-edge technologies such as intelligent video restoration. So that users no longer need to build their own services and functions, they can be used as needed, which greatly reduces development costs.
• Avoid operator differences and complete rapid distribution: relying on a large number of node branches of cloud service providers, covering all operators, and providing intelligent scheduling and edge caching functions. It can quickly distribute application content and improve website response speed.

So what is the difference between AI video cloud and narrowband HD?

Compared with narrowband HD, AI video cloud is more convenient to use, and can be used more in line with user scenarios. Relying on the intelligent features of AI, the AI video cloud will continuously adjust automatically, and there will be no problem of replacement.

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