The Basic Features of VVenC

If you are a CG artist, VVenC may be your best choice. It is an open-source video encoding system that features many features, including Rate control, Subjective quality optimization, Multi-threading, and Open source. Before buying this edition, you should test it out. However, it would help if you remembered that this version is still in development, and its functionality is limited. This article will explain the basic features of VVenC and the pros and cons of each.

Open source encoder

A new version of a free video codec called an open-source VVC encoder has just been made available. This new version aims to achieve higher running speeds, support for multiple threading, Single/Two-stage code control, and subjective quality optimization. The following are some of the critical features of VVenC. If you’d like to try it out, download the latest release and get started.

The VVenC encoder supports the Main10-4.4:4 configuration file, which handles slice code processing. It does not support two-way weighted prediction, but it does support Chinese. It also supports YUV formats, and future versions will also help them. To download the latest version, visit the VVC website. On its website, you can read a detailed review of this open-source encoder for vvenc.

Open-source encoders are freely available, and many of them support a variety of video compression standards. Open-source video encoders allow developers to test various methods before deciding on a specific implementation. It helps determine the best video compression method for a particular use case. You can also try VVenC if you need clarification on whether this standard suits your needs.

As a result, it’s essential to check out the royalty rate of VVC before deciding on a final version. It will take some time for a VVC player to reach a critical mass, but it’s worth looking for content publishers. In the meantime, bandwidth costs will make it harder to justify a new codec. However, it’s still essential to analyze the advantages of this technology in your video workflow.

Rate control

One of the most significant improvements VVenC brings is the ability to use rate control to increase the bit rate. The user can raise the bit rate by making minor adjustments to the encoder from 2.5 to 7.1 or 7.4 bytes. We can also use this mode for audio encoding and frequently for video coding, but several ways could enhance this approach.

It is also possible to adjust the rate while transcoding. We can use the VVenC source code to enable this capability. VVenC supports the Main10-4:4:4 configuration file, which handles slice code processing. This version is not just for the US or the UK; it also supports Chinese input and output. We will add support for YUV to version 1.1.2 shortly. The VVenC encoder also features a streamlined user interface and an easier-to-use graphical user interface.

Besides rate control, this version also includes the JVET CTC, which uses a sequence-specific configuration to optimize bit allocation. The VVC Test Model 3.0 has the optimization procedure in place. The increased speed and accuracy are made possible by effective bit allocation. A detailed comparison of these two software versions shows that it can save 1.03% of BD-Rate while achieving higher control accuracy. You can download the latest release here:

The latest version of the VVenC video codec includes a novel rate control algorithm based on rate-distortion characteristics. This algorithm incorporates a composite Cauchy distribution to provide higher accuracy than other distributions. Furthermore, the rate control algorithm also contains theoretically derived models to model the dependency between levels of frames. This approach improves both the accuracy and performance of rate control. XPSNR is more accurate than the previous version compared to traditional least-squares algorithms.

With several use cases in mind, it developed the VVC standard. High-definition videos are among the many content categories for which it provides unwavering support. Compared to the reference software, the open-source VVenC encoder implementation intends to provide a speedier runtime. Some of its essential characteristics are rate control, multiple threading, and subjective quality enhancements. For random-access, high-resolution video encoding, this encoder is designed. Moreover, we can also configure it for use in different content types and configurations.

Subjective quality optimization

In addition to the usual objective tests, VVenC incorporates an xPSNR-based subjective quality optimization. This metric overcomes the limited correlation between perceived and factual distortions by utilizing a simplified human visual system model. It also implements local quantization parameter adaptations (QPA), which improve rate control accuracy and performance. We conducted three subjective experiment sessions using the test sequences in each of the three resolution groups.

Unlike HEVC, the VVC codec can achieve a VTM level of subjective quality by reducing bit rates by as much as 40% for HD and 50% for UHD. The adaptive bit rate test case also employed objective and subjective quality metrics. The results indicate that the new codecs have improved the video quality of the encoded content. The algorithm can also support multithreaded operations and runtime scaling.

Open-source encoders can also benefit from the VVC standard. Compared to VVC reference software, VVenC can run faster. It also supports multiple threading, rate control, and subjective quality optimization. We can also configure it for different content types and configurations. However, this does not necessarily mean that VVenC is faster than VVC. Instead, it’s a more flexible and extensible standard that enables many use cases.

A brat’s predecessor, High-Efficiency Video Coding (HEVC), was finalized in July 2020. In addition, VVC reference software has reported a 40% bit-rate reduction compared to HEVC reference software, implying a 9x encoding and decoding speed.


Multithreading is a standard programming practice that separates concurrent from parallel processing. For instance, when working with spreadsheets, it is typical for the file to be saved multiple times. The creation of numerous threads in this situation allows them to do various tasks independently. In general, threading is an efficient way to speed up a program. Here are some common examples of multithreading in Vvenc.

For example, you can use mutex if you are trying to compare two pairs of images using a single image. This method prevents multiple threads from accessing the same piece of data simultaneously. For example, if one line has the token A, the other cannot. Then, each thread must wait for the other to release the token. The mutex is a synchronization mechanism that prevents the simultaneous access of two lines to a single object.

A reduced model of the human visual system requires low-complexity quantization, which VVenC enables. In addition, it uses XPSNR and MS-SSIMYUV as subjective video quality measures. Another essential component of VVenC is adaptive resolution. These are just a few of this multithreaded library’s features. You are welcome to see for yourself!

Another popular feature of VVenC is its ability to support multiple threads simultaneously. Unlike traditional multitasking, which involves one thread executing until a long latency event blocks it, multithreaded acceleration allows for high-speed execution. Coarse-grained multitasking is the name of this functionality. It is the right one for you if you’re looking for an open-source encoder that provides multithreaded acceleration.

The multithreaded approach allows applications to take advantage of the power of several processors. It also enables multiple threads to share a memory, which allows the program to take advantage of more of the CPU. It is essential for AI, which relies on human decision-making. Human reaction time is 0.25 seconds, while AI must make decisions in as little as a tenths of a second. Multithreading in C is the ideal solution to make these decisions in time.

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