Apple inc. (20240179336). STREAMED PROGRESSIVE DECODING OF HEIF IMAGES simplified abstract
Contents
- 1 STREAMED PROGRESSIVE DECODING OF HEIF IMAGES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 STREAMED PROGRESSIVE DECODING OF HEIF IMAGES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.9.1 Unanswered Questions
- 1.9.2 How does this technology compare to existing image encoding techniques in terms of compression efficiency and image quality?
- 1.9.3 What are the potential limitations or challenges of implementing these improved still image encoding techniques in real-world applications?
- 1.10 Original Abstract Submitted
STREAMED PROGRESSIVE DECODING OF HEIF IMAGES
Organization Name
Inventor(s)
Alexandros Tourapis of Los Gatos CA (US)
STREAMED PROGRESSIVE DECODING OF HEIF IMAGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240179336 titled 'STREAMED PROGRESSIVE DECODING OF HEIF IMAGES
Simplified Explanation
The abstract of the patent application describes improved still image encoding techniques that involve generating log items and coded tile-layer image data items, with the log enumerating coding quality levels contained in the image data. The image data includes independent-type items, derived-type items of identity variant, and derived-type items with other variant(s), allowing for progressive decoding and spatially variable encoding quality levels.
- Log items and coded tile-layer image data items are generated for improved still image encoding techniques.
- The log enumerates coding quality levels contained in the image data.
- The image data includes independent-type items, derived-type items of identity variant, and derived-type items with other variant(s).
- These techniques enable progressive decoding of images and spatially variable encoding quality levels.
Potential Applications
Improved still image encoding techniques can be applied in various fields such as:
- Digital photography
- Medical imaging
- Satellite imaging
- Video streaming
Problems Solved
These techniques address the following issues:
- Efficient image compression
- Progressive decoding for faster viewing
- Spatially variable encoding quality for optimized image quality
Benefits
The benefits of these techniques include:
- Enhanced image quality
- Reduced file sizes
- Faster image loading times
- Improved user experience
Potential Commercial Applications
Potential commercial applications of these techniques include:
- Image editing software
- Cloud storage services
- Video conferencing platforms
- Online streaming services
Possible Prior Art
One possible prior art in this field is the use of JPEG and JPEG2000 image compression standards for still image encoding.
Unanswered Questions
How does this technology compare to existing image encoding techniques in terms of compression efficiency and image quality?
The article does not provide a direct comparison with existing image encoding techniques in terms of compression efficiency and image quality.
What are the potential limitations or challenges of implementing these improved still image encoding techniques in real-world applications?
The article does not address the potential limitations or challenges of implementing these techniques in real-world applications.
Original Abstract Submitted
improved still image encoding techniques may include generating first items of a log and second items of coded tile-layer image data, where the log enumerates coding quality levels contained in the second items. the second items may include independent-type items, derived-type items of identity variant, and derived-type items with other variant(s). such encoding techniques may provide for progressive decoding of images, and may provide for spatially variable encoding quality levels.
