Boe technology group co., ltd. (20240177271). Image Processing Method, Electronic Device and Non-Transient Computer Readable Medium simplified abstract
Contents
- 1 Image Processing Method, Electronic Device and Non-Transient Computer Readable Medium
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Image Processing Method, Electronic Device and Non-Transient Computer Readable Medium - 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 How does this method compare to existing image enhancement techniques?
- 1.11 What are the limitations of this image processing method?
- 1.12 Original Abstract Submitted
Image Processing Method, Electronic Device and Non-Transient Computer Readable Medium
Organization Name
boe technology group co., ltd.
Inventor(s)
Pablo Navarrete Michelini of Beijing (CN)
Image Processing Method, Electronic Device and Non-Transient Computer Readable Medium - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240177271 titled 'Image Processing Method, Electronic Device and Non-Transient Computer Readable Medium
Simplified Explanation
The abstract describes an image processing method using a trained multi-scale detail enhancement model to enhance details in an input image. The method involves performing multi-scale decomposition on the input image to obtain a base layer image and at least one detail layer image. Residual features corresponding to feature maps are acquired, and base layer output image and detail layer output images are obtained based on these features. Image fusion is then performed to obtain an output image.
- Trained multi-scale detail enhancement model used for detail enhancement
- Multi-scale decomposition performed on input image to obtain base layer and detail layer images
- Acquisition of residual features corresponding to feature maps
- Generation of base layer output image and detail layer output images based on residual features and feature maps
- Image fusion to obtain final output image
Potential Applications
This technology can be applied in various fields such as photography, medical imaging, satellite imaging, and video processing.
Problems Solved
- Enhances details in images for better visual quality - Improves image processing efficiency - Provides a method for multi-scale decomposition and detail enhancement
Benefits
- Enhanced image quality - Improved image processing results - Versatile application in different industries
Potential Commercial Applications
- Image editing software
- Medical imaging devices
- Surveillance systems
- Satellite imaging technology
Possible Prior Art
There are existing methods for image enhancement and detail enhancement in image processing, but the specific combination of multi-scale decomposition, residual features, and image fusion as described in this patent application may be novel.
Unanswered Questions
How does this method compare to existing image enhancement techniques?
This article does not provide a direct comparison with other image enhancement techniques in terms of performance, efficiency, or quality of results.
What are the limitations of this image processing method?
The article does not mention any potential limitations or constraints of the proposed image processing method.
Original Abstract Submitted
an image processing method, comprising: by using a trained multi-scale detail enhancement model, performing detail enhancement on an input image to be processed; wherein multi-scale decomposition is performed on the input image to obtain a base layer image and at least one detail layer image; a first residual feature corresponding to a first feature map is acquired, and a second residual feature corresponding to a second feature map of each detail layer image is acquired; a base layer output image is obtained according to the first residual feature, each second residual feature and the first feature map, and a detail layer output image corresponding to the detail layer image is obtained according to the first residual feature, each second residual feature and the second feature map; and image fusion is performed on the base layer output image and each detail layer output image to obtain an output image.