18303210. METHOD AND APPARATUS WITH SUPERSAMPLING simplified abstract (Samsung Electronics Co., Ltd.)
Contents
- 1 METHOD AND APPARATUS WITH SUPERSAMPLING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS WITH SUPERSAMPLING - 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
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
METHOD AND APPARATUS WITH SUPERSAMPLING
Organization Name
Inventor(s)
Jaeyoung Moon of Suwon-si (KR)
Hyeonseung Yu of Suwon-si (KR)
Hwiryong Jung of Suwon-si (KR)
METHOD AND APPARATUS WITH SUPERSAMPLING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18303210 titled 'METHOD AND APPARATUS WITH SUPERSAMPLING
Simplified Explanation
The abstract describes a method and apparatus for supersampling a low-resolution three-dimensional image by using a neural network to generate a high-resolution image of the previous frame and then replacing parts of it with image data from the current frame.
- Receiving a low-resolution three-dimensional image comprising a current frame and a previous frame.
- Generating a low-resolution partial image by sampling sub-pixel regions of the current frame.
- Warping a high-resolution image of the previous frame to the current view.
- Replacing a partial region of the warped high-resolution image with image data from the low-resolution partial image.
- Generating a high-resolution image of the current frame by applying the modified high-resolution image of the previous frame to the neural network.
Potential Applications
This technology could be applied in video games, virtual reality, medical imaging, and surveillance systems.
Problems Solved
This technology solves the problem of generating high-resolution images from low-resolution inputs in real-time applications.
Benefits
The benefits of this technology include improved image quality, enhanced visual experience, and faster processing speeds.
Potential Commercial Applications
Potential commercial applications of this technology include video game development, medical imaging software, virtual reality systems, and security surveillance solutions.
Possible Prior Art
One possible prior art for this technology could be the use of neural networks for image upscaling and enhancement in various fields such as photography and video processing.
Unanswered Questions
How does this method compare to traditional supersampling techniques?
Answer: This article does not provide a direct comparison between this method and traditional supersampling techniques. It would be interesting to know the performance differences and advantages of this approach over conventional methods.
What are the computational requirements for implementing this method?
Answer: The article does not mention the computational resources needed to implement this method. Understanding the computational demands could be crucial for assessing the feasibility of integrating this technology into different systems.
Original Abstract Submitted
A supersampling method and apparatus are provided. The method includes: receiving a low-resolution three-dimensional (3D) image comprising a current frame and receiving a previous frame preceding the current frame; generating a low-resolution partial image by repeatedly sampling sub-pixel regions of the current frame; warping a high-resolution image, of the previous frame, which has been outputted from a neural network, to a current view corresponding to the current frame; replacing a partial region of the warped high-resolution image of the previous frame with image data from the low-resolution partial image; and generating a high-resolution image of the current frame by applying the high-resolution image of the previous frame, in which the partial region has been replaced, to the neural network.
