18585957. HIGH-RESOLUTION IMAGE GENERATION simplified abstract (ADOBE INC.)
Contents
HIGH-RESOLUTION IMAGE GENERATION
Organization Name
Inventor(s)
Tobias Hinz of Campbell CA (US)
Taesung Park of San Francisco CA (US)
Jingwan Lu of Sunnyvale CA (US)
Elya Shechtman of Seattle WA (US)
Richard Zhang of Burlingame CA (US)
Oliver Wang of Seattle WA (US)
HIGH-RESOLUTION IMAGE GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18585957 titled 'HIGH-RESOLUTION IMAGE GENERATION
Simplified Explanation: This patent application describes a method, system, and apparatus for generating high-resolution images from low-resolution images with random noise.
Key Features and Innovation:
- Obtaining an input image with random noise and generating a low-resolution image with the same resolution.
- Generating a high-resolution image from the low-resolution image with a greater resolution.
- Enhancing image quality and resolution through a multi-step process.
Potential Applications: This technology could be used in various fields such as medical imaging, satellite imaging, surveillance systems, and digital photography.
Problems Solved:
- Improving image quality and resolution.
- Enhancing the clarity and detail of images with random noise.
- Providing a more efficient method for generating high-resolution images.
Benefits:
- Enhanced image quality and resolution.
- Improved accuracy in image analysis and interpretation.
- Increased usability of images in various applications.
Commercial Applications: The technology could be utilized in industries such as healthcare, defense, photography, and remote sensing for commercial purposes.
Prior Art: Researchers can explore prior art related to image processing, noise reduction, and image enhancement techniques to understand the existing technology landscape.
Frequently Updated Research: Stay updated on advancements in image processing algorithms, machine learning techniques, and computer vision research related to high-resolution image generation.
Questions about Image Generation: 1. How does this technology compare to traditional image upscaling methods? 2. What are the potential limitations of generating high-resolution images from low-resolution inputs?
Original Abstract Submitted
A method, non-transitory computer readable medium, apparatus, and system for image generation include obtaining an input image having a first resolution, where the input image includes random noise, and generating a low-resolution image based on the input image, where the low-resolution image has the first resolution. The method, non-transitory computer readable medium, apparatus, and system further include generating a high-resolution image based on the low-resolution image, where the high-resolution image has a second resolution that is greater than the first resolution.
