1. Pixel super resolution imaging method based on coded aperture modulation
- Author
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Chao Zuo, Jiasong Sun, Hu Yan, Bowen Wang, and Yan Zou
- Subjects
Pixel ,business.industry ,Computer science ,Aperture ,Detector ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Pixelation ,Computer Science::Computer Vision and Pattern Recognition ,Imaging technology ,Nyquist–Shannon sampling theorem ,Computer vision ,Artificial intelligence ,Coded aperture ,business ,Image resolution - Abstract
In recent years, the development of computational imaging technology provides a new method for the realization of non-scanning super-resolution imaging. In this paper, a pixel super-resolution algorithm based on Fourier ptychographic technology is proposed, and the corresponding integrated and systematic programmable aperture coded super-resolution imaging system is constructed. By modulating the intensity with the coded aperture mask, utilizing different system point spread functions to obtain multiple samples of the original scene, and finally adopting sparse optimization iterative algorithm to reconstruct the original image, the result of super- resolution imaging is more than 3.5 times of Nyquist sampling frequency. In this tutorial, the proposed new super-resolution photoelectric imaging technology innovatively adopts the approach of coded aperture to realize image super-resolution imaging and effectively solve image pixelation. High-resolution images beyond the spatial resolution of the detector are obtained without any physical moving device or scanning mechanism. Compared with the traditional micro-scanning technology, it not only improves the reliability and stability of the system but also greatly reduces the cost and volume weight of the system.
- Published
- 2021