Enhancing image quality of ghost imaging by fuzzy c-means clustering method
Source abstract
Abstract
We presented a novel ghost imaging scheme based on fuzzy c-means clustering (FCM) to reduce measurements and improve the visibility of the reconstruction image. Different from the GI methods, the FCM model is first employed to partition the intensity values of the reference light path and probe light path. Then, the relative speckle patterns and bucket intensity values are selected with respect to the clustering results. Finally, the object can be obtained by conventional GI methods. From the considerable simulations and experimental results, we conclude that the proposed scheme can enhance the visibility of the reconstruction image by using much fewer data from measurements compared with the existing GI methods.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Random lasers and scattering media · Image and Video Quality Assessment · Advanced Optical Imaging Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University 1 , Changchun 130012, China
School of Physics, Northeast Normal University 2 , Changchun 130024, China
Chanchun Institute of Technology, School of Electrical Engineering and InformationTechnology 3 , Changchun 130012, China
Funding
the · the Foundation for Excellent Young Talents of Jilin Province · China Postdoctoral Science Foundation · National Natural Science Foundation of China
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