18609623. INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND SYSTEM simplified abstract (CANON KABUSHIKI KAISHA)
Contents
INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND SYSTEM
Organization Name
Inventor(s)
YOSUKE Takada of Kanagawa (JP)
INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18609623 titled 'INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND SYSTEM
The abstract describes an information processing apparatus that utilizes a trained neural network to reduce noise in an image. The apparatus adjusts the black floating of an input image to match the black floating of an image used during the neural network training, then performs inference processing on the noise-reduced image using the trained neural network.
- The apparatus is configured to reduce noise in images using a trained neural network.
- It adjusts the black floating of input images to match the black floating of images used during training.
- Inference processing is performed on the noise-reduced images using the trained neural network.
- The neural network is specifically trained to suppress the black floating in images.
Potential Applications: - Image processing and enhancement in photography - Medical imaging for clearer diagnostics - Video processing for improved quality - Surveillance systems for better image analysis - Satellite imaging for enhanced data extraction
Problems Solved: - Reduction of noise in images - Improvement of image quality - Consistency in black floating adjustment - Enhanced accuracy in image analysis - Efficient processing of noisy images
Benefits: - Enhanced image quality - Improved accuracy in image analysis - Consistent black floating adjustment - Efficient noise reduction in images - Enhanced visual clarity in various applications
Commercial Applications: Title: "Advanced Image Processing Technology for Enhanced Visual Quality" This technology can be utilized in industries such as photography, healthcare, security, entertainment, and satellite imaging. It can improve image quality, accuracy in analysis, and overall visual clarity, leading to better products and services in these sectors.
Questions about the technology: 1. How does the trained neural network differentiate between noise and actual image data? 2. What are the potential limitations of using this technology in real-time applications?
Original Abstract Submitted
An information processing apparatus configured to reduce noise in an image using a trained neural network includes at least one processor and at least one memory having instructions stored thereon that, when executed by the at least one processor, cause the at least one processor and the at least one memory to cooperate to adjust a black floating of an input image so as to be closer to a black floating of an image used at a time of training of the neural network, and perform inference processing on a noise-reduced image of the adjusted image, using the neural network trained to suppress the black floating.
