Google llc (20240320808). Learning-Based Lens Flare Removal simplified abstract
Contents
Learning-Based Lens Flare Removal
Organization Name
Inventor(s)
Qiurui He of Mountain View CA (US)
Tianfan Xue of Sunnyvale CA (US)
Rahul Garg of Sunnyvale CA (US)
Jiawen Chen of San Ramon CA (US)
Jonathan T. Barron of Alameda CA (US)
Learning-Based Lens Flare Removal - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320808 titled 'Learning-Based Lens Flare Removal
The patent application describes a method that involves using a machine learning model to remove lens flare from an input image.
- The method includes obtaining an input image with lens flare representation.
- The input image is processed by a machine learning model to generate a de-flared image.
- The machine learning model is trained using training images that combine baseline images with corresponding lens flare images.
- Parameters of the machine learning model are adjusted based on the loss value determined for each training image.
Potential Applications: - Photography post-processing software - Image editing applications - Computer vision systems for image enhancement
Problems Solved: - Removing lens flare from images - Improving image quality and aesthetics - Automating the process of lens flare removal
Benefits: - Enhanced image quality - Time-saving in post-processing - Consistent and accurate lens flare removal
Commercial Applications: Title: "AI-Powered Lens Flare Removal Technology for Image Editing Software" This technology can be used in commercial image editing software to provide users with a quick and efficient way to remove lens flare from their photos. It can be marketed as a feature that enhances the overall quality of images and saves time for photographers and graphic designers.
Prior Art: Prior art related to this technology may include research papers or patents on image processing techniques, machine learning models for image enhancement, and software tools for removing lens flare from images.
Frequently Updated Research: Researchers may be continuously working on improving machine learning models for image processing, developing new algorithms for lens flare removal, and exploring applications of artificial intelligence in photography.
Questions about Lens Flare Removal Technology: 1. How does the machine learning model differentiate between lens flare and other elements in the image? 2. What are the potential limitations of using this technology in real-time image processing applications?
Original Abstract Submitted
a method includes obtaining an input image that contains a particular representation of lens flare, and processing the input image by a machine learning model to generate a de-flared image that includes the input image with at least part of the particular representation of lens flare removed. the machine learning (ml) model may be trained by generating training images that combine respective baseline images with corresponding lens flare images. for each respective training image, a modified image may be determined by processing the respective training image by the ml model, and a loss value may be determined based on a loss function comparing the modified image to a corresponding baseline image used to generate the respective training image. parameters of the ml model may be adjusted based on the loss value determined for each respective training image and the loss function.
