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Super-resolution compressed sensing imaging algorithm based on sub-pixel shift
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AI
DOI：10.1007/s10586-018-1839-2.png)
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Abstract
En 中文
At present, some digital signal processing methods have attracted more and more attention in improving the resolution of images. Sub-pixel shift has been widely applied in improving the resolution of compressed sensing imaging system. The resolution of the compressed sensing imaging system is limited by pixel size of the modulation system. To overcome the resolution limitation of compressed sensing imaging system, a sub-pixel shift method is proposed to enhance the resolution of modulation information and achieve super-resolution images by compressed sensing imaging system. The principle of the proposed method is introduced and the proposed method is verified using numerical simulations. Experimental results revealed that the proposed method can effectively improve the resolution of compressed sensing imaging system and obtain super-resolution image information. Additionally, the signal to noise ratio of restoration results is positively related to the sample size.
Keywords:
Compressed sensing
Super-resolution
Sub-pixel shift
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