Intel corporation (20240214594). VIDEO CODEC ASSISTED REAL-TIME VIDEO ENHANCEMENT USING DEEP LEARNING simplified abstract
Contents
VIDEO CODEC ASSISTED REAL-TIME VIDEO ENHANCEMENT USING DEEP LEARNING
Organization Name
Inventor(s)
Ximin Zhang of San Jose CA (US)
Yi-Jen Chiu of San Jose CA (US)
Sang-Hee Lee of San Jose CA (US)
VIDEO CODEC ASSISTED REAL-TIME VIDEO ENHANCEMENT USING DEEP LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240214594 titled 'VIDEO CODEC ASSISTED REAL-TIME VIDEO ENHANCEMENT USING DEEP LEARNING
The abstract discusses techniques related to accelerated video enhancement using deep learning selectively applied based on video codec information. These techniques include applying a deep learning video enhancement network selectively to decoded non-skip blocks in low quantization parameter frames, bypassing the deep learning network for decoded skip blocks in low quantization parameter frames, and applying non-deep learning video enhancement to high quantization parameter frames.
- Selective application of deep learning video enhancement based on video codec information
- Enhancing decoded non-skip blocks in low quantization parameter frames using deep learning
- Bypassing deep learning network for decoded skip blocks in low quantization parameter frames
- Applying non-deep learning video enhancement to high quantization parameter frames
Potential Applications: - Improving video quality in low quantization parameter frames - Enhancing video compression efficiency - Enhancing video streaming quality
Problems Solved: - Addressing the need for efficient video enhancement techniques - Improving video quality selectively based on codec information
Benefits: - Enhanced video quality in specific frames - Improved video compression efficiency - Enhanced user experience in video streaming
Commercial Applications: Title: Enhanced Video Quality Technology for Video Streaming Services Potential commercial uses include video streaming platforms, video compression software, and video editing tools. This technology can improve the quality of videos streamed online, leading to better user engagement and satisfaction.
Questions about the Technology: 1. How does this technology impact video compression efficiency? 2. What are the potential applications of selectively applying deep learning video enhancement based on codec information?
Frequently Updated Research: Stay updated on advancements in deep learning techniques for video enhancement and improvements in video codec technology to enhance the application of this technology.
Original Abstract Submitted
techniques related to accelerated video enhancement using deep learning selectively applied based on video codec information are discussed. such techniques include applying a deep learning video enhancement network selectively to decoded non-skip blocks that are in low quantization parameter frames, bypassing the deep learning network for decoded skip blocks in low quantization parameter frames, and applying non-deep learning video enhancement to high quantization parameter frames.
