18404696. VIDEO CODEC ASSISTED REAL-TIME VIDEO ENHANCEMENT USING DEEP LEARNING simplified abstract (Intel Corporation)
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 18404696 titled 'VIDEO CODEC ASSISTED REAL-TIME VIDEO ENHANCEMENT USING DEEP LEARNING
- Simplified Explanation:**
The patent application discusses techniques for accelerated video enhancement using deep learning, selectively applied based on video codec information.
- Key Features and Innovation:**
- Applying 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.
- Applying non-deep learning video enhancement to high quantization parameter frames.
- Potential Applications:**
This technology can be applied in video processing, video streaming services, video editing software, and video surveillance systems.
- Problems Solved:**
The technology addresses the need for efficient video enhancement techniques tailored to specific video codec information, improving video quality and reducing processing time.
- Benefits:**
- Enhanced video quality in low quantization parameter frames.
- Faster video processing for improved efficiency.
- Tailored video enhancement based on codec information.
- Commercial Applications:**
- "Accelerated Video Enhancement Using Deep Learning" technology can be utilized in video editing software to provide users with advanced enhancement options.
- It can also be integrated into video streaming services to improve the quality of streamed content, enhancing user experience and attracting more subscribers.
- Questions about Accelerated Video Enhancement Using Deep Learning:**
1. How does this technology improve video quality in low quantization parameter frames? 2. What are the potential commercial applications of this technology in the video processing industry?
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.
