Boe technology group co., ltd. (20240202891). METHOD FOR TRAINING IMAGE PROCESSING MODEL, AND METHOD FOR GENERATING HIGH DYNAMIC RANGE IMAGE simplified abstract
Contents
METHOD FOR TRAINING IMAGE PROCESSING MODEL, AND METHOD FOR GENERATING HIGH DYNAMIC RANGE IMAGE
Organization Name
boe technology group co., ltd.
Inventor(s)
METHOD FOR TRAINING IMAGE PROCESSING MODEL, AND METHOD FOR GENERATING HIGH DYNAMIC RANGE IMAGE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202891 titled 'METHOD FOR TRAINING IMAGE PROCESSING MODEL, AND METHOD FOR GENERATING HIGH DYNAMIC RANGE IMAGE
- Simplified Explanation:**
The patent application describes a method for training an image processing model to enhance low dynamic range images by generating high dynamic range reconstructions.
- Key Features and Innovation:**
- Inputting a low dynamic range image into an initial image processing model for high dynamic range reconstruction.
- Generating a first high dynamic range image and a first coefficient from the low dynamic range image.
- Creating a second high dynamic range image using the first image and coefficient.
- Generating a loss function based on pairs of the second high dynamic range image and a real high dynamic range image.
- Training the initial image processing models with the loss function.
- Potential Applications:**
This technology can be used in various fields such as photography, medical imaging, satellite imaging, and surveillance systems to enhance image quality and detail.
- Problems Solved:**
This technology addresses the challenge of enhancing low dynamic range images to high dynamic range images, improving image quality and detail.
- Benefits:**
- Improved image quality and detail.
- Enhanced visualization in various applications.
- Better performance in image processing tasks.
- Commercial Applications:**
Enhancing image quality in photography, medical imaging, satellite imaging, and surveillance systems can lead to improved products and services in these industries.
- Questions about Image Processing:**
1. How does this method improve the quality of low dynamic range images?
- This method enhances low dynamic range images by generating high dynamic range reconstructions through a series of processing steps.
2. What are the potential applications of training image processing models with this method?
- The potential applications include improving image quality in photography, medical imaging, satellite imaging, and surveillance systems.
Original Abstract Submitted
a method for training an image processing model includes: inputting a low dynamic range image into a first initial image processing model, so that a high dynamic range reconstruction processing is performed on the low dynamic range image to generate a first high dynamic range image; inputting the low dynamic range image into a second initial image processing model to generate a first coefficient; generating a second high dynamic range image according to the first high dynamic range image and the first coefficient; generating a loss function according to data pairs of the second high dynamic range image and a real high dynamic range image, the real high dynamic range image corresponding to the low dynamic range image; and training the first initial image processing model and the second initial image processing model with the loss function.
