18091239. METHOD AND APPARATUS WITH IMAGE RESTORATION simplified abstract (Samsung Electronics Co., Ltd.)
Contents
METHOD AND APPARATUS WITH IMAGE RESTORATION
Organization Name
Inventor(s)
Jaehyoung Yoo of Suwon-si (KR)
Hyong Euk Lee of Suwon-si (KR)
METHOD AND APPARATUS WITH IMAGE RESTORATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18091239 titled 'METHOD AND APPARATUS WITH IMAGE RESTORATION
Simplified Explanation
The abstract describes a method and apparatus for image restoration using a neural network-based model. Here is a simplified explanation of the abstract:
- The method involves filtering target data with multiple filter kernels to determine auxiliary data.
- The auxiliary data is combined with input data from layers of a neural network-based image restoration model to determine new input data.
- The new input data is used to generate a restored image of the input image by executing the neural network-based image restoration model.
- The filter kernels used in the method are not part of the neural network-based image restoration model.
Potential Applications:
- Image Restoration: The technology can be used to restore and enhance images by removing noise, artifacts, or other imperfections.
- Medical Imaging: It can be applied to improve the quality and clarity of medical images, aiding in diagnosis and treatment.
- Surveillance and Security: The method can enhance low-quality surveillance footage, improving visibility and identifying important details.
- Photography and Graphic Design: It can be used to enhance and restore old or damaged photographs, as well as improve the quality of digital images.
Problems Solved:
- Image Degradation: The technology addresses the problem of image degradation caused by noise, blur, or other factors, restoring the image to its original quality.
- Imperfections and Artifacts: It helps in removing imperfections, artifacts, and distortions from images, resulting in a cleaner and more visually appealing output.
Benefits:
- Improved Image Quality: The method enhances the quality of images by effectively combining auxiliary data and input data from a neural network-based model.
- Versatility: The technology can be applied to various domains, including photography, medical imaging, surveillance, and more.
- Efficiency: By using filter kernels separately from the neural network-based model, the method may offer faster and more efficient image restoration compared to traditional approaches.
Original Abstract Submitted
An image restoration method and apparatus are provided. The image restoration method includes determining auxiliary data corresponding to a plurality of filter kernels by filtering target data with the plurality of filter kernels, determining new input data by combining the auxiliary data with at least some input data of layers of a neural network-based image restoration model, generating, based on the new input data, a restored image of the input image by executing the neural network-based image restoration model, wherein the filter kernels are not part of the neural network-based image restoration model.
