A hyperspectral image compression method based on joint spatial-spectral compressive sensing
By combining spatial spectral domain compressed sensing and deep learning algorithms, the problem of limited infrared spectral image resolution was solved, and efficient high-resolution infrared spectral image reconstruction was achieved.
CN119399630BActive Publication Date: 2025-11-04BEIJING INST OF TECH
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Patent Information
- Application Number
- CN202411468031.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-21
- Publication Date
- 2025-11-04
- Estimated Expiration
- 2044-10-21
AI Technical Summary
Technical Problem
Existing technologies struggle to acquire both high spatial and high spectral resolution infrared spectral images simultaneously. Infrared detectors suffer from low spatial resolution and limited spectral resolution, resulting in significant data transmission and storage challenges.
Method used
A spatial-spectral domain joint compressed sensing method is adopted, which utilizes DMD and diffraction gratings for spatial and spectral modulation, and combines deep learning reconstruction algorithms to generate high-resolution infrared spectral images.
Benefits of technology
It enables the reconstruction of infrared spectral images with high spatial and spectral resolution, reduces data acquisition, storage, and transmission, and improves imaging efficiency.
✦ Generated by Eureka AI based on patent content.
Abstract
The application discloses a kind of space spectral domain joint compression sensing method for infrared spectrum image, belong to high resolution spectral imaging and compression imaging field.The method for realizing the application is: generating space spectral domain joint compression imaging encoding matrix, this matrix is used as encoding template and is loaded to DMD, so that it is modulated to target light information in space, using diffraction grating to modulate spectral image after spatial modulation, using low-resolution infrared camera to modulate the image after space and spectrum downsampling, obtain low-resolution two-dimensional aliasing image.Through space compression imaging and spectral compression imaging, the limitation of infrared camera spatial resolution and spectral resolution is broken through, and the low spatial low spectral resolution infrared image collected can restore the original high spatial high spectral resolution infrared image using reconstruction algorithm.The application utilizes the spatial, spectral correlation of spectral image, and compresses data before data acquisition by compression imaging method, which significantly reduces the data amount of acquisition, storage and transmission.
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