High resolution multi scene infrared database
Welcome to use the High resolution multi scene infrared database in Raytron database
Time:2024-05-13 Font A- A A+
With the widespread application of infrared imaging technology in various fields, infrared image super-resolution has become a key technology that can improve image quality and extract more information. However, infrared images typically have lower resolution, limiting their details and texture information, and are more prone to noise during the imaging process, which further reduces image quality. In addition, the acquisition cost of infrared images is relatively high, resulting in fewer scenes in infrared images. These factors greatly limit the performance and generalization ability of infrared super-resolution algorithms.
In order to promote the research and development of infrared image super-resolution technology and solve these problems, we have constructed a multi scene infrared super-resolution image database. This database covers multiple scenarios and conditions to reflect a wide range of practical applications. The resolution of the image is mainly 1280 * 1024, 1920 * 1080, and 640 * 512. High-resolution and high-quality images Provide rich details and texture information. This database is conducive to utilizing high-quality infrared image data from the real world to develop more robust and accurate super-resolution algorithms, promoting the application of infrared super-resolution technology in various fields.
Our research aims to establish a high-resolution multi scene real-world infrared image super-resolution database, providing high-quality real-world data, enabling researchers to evaluate and compare the performance of different super-resolution algorithms, and develop new accurate algorithms. This database contains a total of 7224 images from nine categories of scenes, including sea view images, animal images, industrial scenes, cityscapes, natural landscapes, indoor images, portraits, surveillance image, and vehicle perspective road images. It is divided into a test set of 726 images and a training set of 6498 images, all of which are single channel images saved in BMP format.
The researchers
The study was conducted by:
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Copyright Notice
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Copyright (C) 2021 Yantai Raytron Technology Co., Ltd. All Rights Reserved.
All rights reserved.
Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this database (the images, the results and the source files) and its documentation for any purpose, provided that the copyright notice in its entirety appear in all copies of this database, and the original source of this database, Raytron Technology Co., Ltd ( http://openai.raytrontek.com/ ), is acknowledged in any publication that reports research using this database. In no event shall Yantai Raytron Technology Co., Ltd be liable to any party for direct, indirect, special, incidental or consequential damages arising out of the use of this database and its documentation,even if Yantai Raytron Technology Co., Ltd has been advised of the possibility of such damage.
Yantai Raytron Technology Co., Ltd disclaims any warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose. The database provided hereunder is on an "as is" basis, and Yantai Raytron Technology Co., Ltd has no obligation to provide maintenance, support, updates, enhancements, or modifications.
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Download
We are making the real-world infrared image super-resolution database of infrared images available to the public for free. If you use this database in your research, We would appreciate your appreciation for the research done by our company:
Yantai Raytron Technology Co., Ltd.
You can fill in the above form to submit the application form for using this database to us. After the approval, the download address of this database will be sent to your email.
If you encounter any problems in downloading, viewing or using this database, please contact the maintenance staff of this website:Chunlei Guan( chunlei.guan@raysense.com )
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