18305625. IMAGE PROCESSING DEVICE, ELECTRONIC DEVICE HAVING THE SAME, AND OPERATING METHOD THEREOF simplified abstract (Samsung Electronics Co., Ltd.)
Contents
- 1 IMAGE PROCESSING DEVICE, ELECTRONIC DEVICE HAVING THE SAME, AND OPERATING METHOD THEREOF
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 IMAGE PROCESSING DEVICE, ELECTRONIC DEVICE HAVING THE SAME, AND OPERATING METHOD THEREOF - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
IMAGE PROCESSING DEVICE, ELECTRONIC DEVICE HAVING THE SAME, AND OPERATING METHOD THEREOF
Organization Name
Inventor(s)
Seungwon Choi of Suwon-si (KR)
Jongseong Choi of Suwon-si (KR)
IMAGE PROCESSING DEVICE, ELECTRONIC DEVICE HAVING THE SAME, AND OPERATING METHOD THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 18305625 titled 'IMAGE PROCESSING DEVICE, ELECTRONIC DEVICE HAVING THE SAME, AND OPERATING METHOD THEREOF
Simplified Explanation
The method described in the patent application involves using neural networks to denoise frames in a video sequence. Here is a simplified explanation of the abstract:
- Acquire current frame, noise dispersion map, and first denoised frame for previous frame
- Generate weighted first denoised frame based on input data using first neural network
- Generate initial fused image based on current frame and weighted first denoised frame using second neural network
- Generate second denoised frame for current frame based on initial fused image using third neural network
Potential Applications
This technology could be applied in video processing, surveillance systems, medical imaging, and any other field where denoising of images or video frames is required.
Problems Solved
This technology solves the problem of noise reduction in video sequences, improving the overall quality and clarity of the images.
Benefits
The benefits of this technology include improved image quality, enhanced visual clarity, and better performance in various applications that require denoising of video frames.
Potential Commercial Applications
Potential commercial applications of this technology include video editing software, security systems, medical imaging devices, and any other product or service that involves processing and enhancing video content.
Possible Prior Art
One possible prior art for this technology could be existing denoising algorithms and methods used in image and video processing software. These may include traditional filters, wavelet-based denoising techniques, and other neural network-based denoising approaches.
Unanswered Questions
How does the neural network training process work in this method?
The patent application does not provide details on how the neural networks are trained to perform denoising tasks effectively.
What is the computational cost of implementing this method in real-time applications?
The abstract does not mention the computational resources required to implement this method for denoising video frames in real-time scenarios.
Original Abstract Submitted
A method includes acquiring a current frame, a noise dispersion map for the current frame, and a first denoised frame for a previous frame; generating a weighted first denoised frame based on the noise dispersion map, the current frame, and the first denoised frame using a first neural network; generating an initial fused image based on the current frame and the weighted first denoised frame using a second neural network; and generating a second denoised frame for the current frame based on the initial fused image using a third neural network.
