18064575. IMAGE SIGNAL PROCESSOR AND IMAGE SENSOR INCLUDING THE IMAGE SIGNAL PROCESSOR simplified abstract (Samsung Electronics Co., Ltd.)
Contents
IMAGE SIGNAL PROCESSOR AND IMAGE SENSOR INCLUDING THE IMAGE SIGNAL PROCESSOR
Organization Name
Inventor(s)
IMAGE SIGNAL PROCESSOR AND IMAGE SENSOR INCLUDING THE IMAGE SIGNAL PROCESSOR - A simplified explanation of the abstract
This abstract first appeared for US patent application 18064575 titled 'IMAGE SIGNAL PROCESSOR AND IMAGE SENSOR INCLUDING THE IMAGE SIGNAL PROCESSOR
Simplified Explanation
The patent application describes an image signal processor and an image sensor that work together to convert optical signals into electrical signals and process them using deep learning-based image processing techniques. The image sensor includes a pixel array, a readout circuit, and an image signal processor.
- The pixel array in the image sensor converts received optical signals into electrical signals.
- The readout circuit converts the electrical signals into image data and outputs it.
- The image signal processor performs deep learning-based image processing on the image data.
- The training data used for the image processing is selected based on the noise level of the image data.
- The image processing techniques are based on deep learning, which allows for more advanced and accurate processing of the image data.
Potential applications of this technology:
- Digital cameras and smartphones can benefit from improved image processing capabilities.
- Surveillance systems can utilize the deep learning-based image processing to enhance object recognition and tracking.
- Medical imaging devices can produce higher quality images for diagnosis and analysis.
- Autonomous vehicles can use the technology to improve their perception and understanding of the environment.
Problems solved by this technology:
- Traditional image processing techniques may not be able to effectively handle noise in the image data.
- Deep learning-based image processing can provide more accurate and advanced processing capabilities.
- The selection of training data based on noise level helps optimize the image processing for different scenarios.
Benefits of this technology:
- Improved image quality and accuracy in various applications.
- Enhanced object recognition and tracking capabilities.
- Better performance in low-light or noisy environments.
- Increased efficiency and speed in image processing tasks.
Original Abstract Submitted
An image signal processor and an image sensor including the same are disclosed. An image sensor includes a pixel array configured to convert received optical signals into electrical signals, a readout circuit configured to convert the electrical signals into image data and output the image data, and an image signal processor configured to perform deep learning-based image processing on the image data based on training data selected from among first training data and second training data based on a noise level of the image data.
