Recently, a research team from Hefei Institutes of Physical Science (HFIPS) of Chinese Academy of Sciences (CAS) presented a new anti-motion blur single-pixel imaging method for fast-moving objects. It took advantage of the wide spectrum and high sensitivity of a single-pixel detector and contributed to getting around the bottleneck of single-pixel imaging for fast-moving objects.
This research was selected for the Editor's Pick of Optics Letters.
The method was built upon previous proof-of-principle work for capturing motion information together with imaging information.
"This study changed the traditional belief that single-pixel imaging was only suitable for imaging static or slow-moving objects," said WANG Yingjian, who led the team.
Single-pixel imaging technique has made significant progress in imaging static or slow-moving objects which has been widely recognized. However, for fast-moving objects, motion blur is the main bottleneck of single-pixel imaging in practical engineering applications.
To solve this problem, the research group, combined with the previous research results, proposed an integrated multi-task tackling system for tracking and imaging moving objects. A small amount of information detected by a single-pixel detector is applied to realizing the positioning and tracking of moving objects. With the increase of detection information over time, the imaging of fast-moving objects and the motion blur correction are realized synchronously.
The proposed technology system fully exploited the characteristics of single-pixel detection and realized the rapid positioning, clear imaging, and recognition of fast-moving targets according to the characteristics of the system's detection information data stream. The proposed "tracking before imaging" technical roadmap subverts the time sequence relationship of imaging before tracking in the traditional technical method.
"The experimental results are encouraging," said Dr. Matthew Edgar, formerly University of Glasgow, "and I am sure future work in this area will compare and contrast the efficacy of the author's approach with other single-pixel sampling and reconstruction methods for real-world applications where there is rapid and dynamic motion of objects in the scene."
"With this strategy, rapid tracking of an object is demonstrated," said Professor Randy Bartels from Colorado State University, "This approach has the potential to scale to very high speeds."
Anti-motion blur single-pixel imaging with calibrated radon spectrum
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