17948138. USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE simplified abstract (NVIDIA Corporation)
Contents
- 1 USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE - 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
USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE
Organization Name
Inventor(s)
Shiqiu Liu of Cupertino CA (US)
Jussi Rasanen of Helsinki (FI)
Michael Ranzinger of Park City UT (US)
Guilin Liu of San Jose CA (US)
Andrew Tao of Los Altos CA (US)
Bryan Christopher Catanzaro of Los Altos Hills CA (US)
USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE - A simplified explanation of the abstract
This abstract first appeared for US patent application 17948138 titled 'USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE
Simplified Explanation
The patent application describes using neural networks to generate an upsampled version of images based on denoised versions of the same images. One embodiment involves creating a high-resolution image from a noisy low-resolution image, while another involves separating components of a low-resolution image before denoising.
- Neural networks used to generate upsampled images based on denoised versions.
- Can create high-resolution images from noisy low-resolution images.
- Separates components of low-resolution images before denoising.
Potential Applications
This technology could be applied in:
- Image processing
- Medical imaging
- Satellite imaging
Problems Solved
- Enhances image quality
- Improves image resolution
- Reduces noise in images
Benefits
- Higher quality images
- Enhanced details in images
- Improved image processing capabilities
Potential Commercial Applications
- Photography software
- Medical imaging devices
- Satellite imaging companies
Possible Prior Art
One possible prior art could be the use of neural networks for image processing and denoising, but the specific application of generating upsampled images based on denoised versions may be novel.
Unanswered Questions
How does this technology compare to traditional image upscaling methods?
This article does not compare the performance of this technology with traditional image upscaling methods.
What are the computational requirements for implementing this technology?
The article does not provide information on the computational resources needed to use this technology effectively.
Original Abstract Submitted
Apparatuses, systems, and techniques to use one or more neural networks to generate an upsampled version of one or more images based, at least in part, on a denoised version of said one or more images. At least one embodiment pertains to generating an upsampled high-resolution image from a noisy version and denoised version of a low-resolution image. At least one embodiment pertains to separating components of a low-resolution image before denoising an image.
