18731736. MODE-DEPENDENT JOINT COMPONENT TRANSFORM simplified abstract (Tencent America LLC)
Contents
MODE-DEPENDENT JOINT COMPONENT TRANSFORM
Organization Name
Inventor(s)
Madhu Peringassery Krishnan of Mountain View CA (US)
MODE-DEPENDENT JOINT COMPONENT TRANSFORM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18731736 titled 'MODE-DEPENDENT JOINT COMPONENT TRANSFORM
The patent application describes a method for coding video data using a joint component secondary transformation (JCST) technique.
- Receiving video data
- Entropy-parsing the video data into components
- De-quantizing the components
- Performing a JCST on the components based on selected JCST kernel
- Decoding the video data using residual components from the JCST
Potential Applications: - Video compression technology - Multimedia streaming services - Video editing software
Problems Solved: - Efficient video data compression - Improved video quality - Reduced bandwidth usage in video streaming
Benefits: - Higher compression rates - Enhanced video quality - Reduced data transmission costs
Commercial Applications: Title: Advanced Video Compression Technology for Streaming Services This technology can be used in video streaming platforms to improve video quality and reduce bandwidth costs, making it attractive for companies offering streaming services.
Questions about the technology: 1. How does the JCST technique improve video compression efficiency?
- The JCST technique optimizes the transformation process based on prediction modes and transform types, leading to better compression results.
2. What impact does this technology have on video streaming services?
- This technology can significantly reduce bandwidth usage and improve video quality for streaming platforms, enhancing user experience.
Original Abstract Submitted
A method for coding video data, executable by a processor, includes receiving video data; entropy-parsing the received video data into one or more components; de-quantizing the one or more entropy-parsed components; performing a joint component secondary transformation (JCST) on the one or more components in accordance with a JCST kernel selected based on one of (i) a prediction mode corresponding to the video data, (ii) a primary transform type of a current block, and (iii) a secondary transform kernel selected for the current block; and decoding the video data based on one or more residual components corresponding to the joint component secondary transformed components.
