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Fast autofocusing based on single-pixel moment detection.
Chen, Huiling; Shi, Dongfeng; Guo, Zijun; Jiang, Runbo; Zha, Linbin; Wang, Yingjian; Flusser, Jan.
Affiliation
  • Chen H; School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, 230026, China.
  • Shi D; Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.
  • Guo Z; School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, 230026, China. dfshi@aiofm.ac.cn.
  • Jiang R; Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China. dfshi@aiofm.ac.cn.
  • Zha L; Advanced Laser Technology Laboratory of Anhui Province, Hefei, 230037, China. dfshi@aiofm.ac.cn.
  • Wang Y; School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, 230026, China.
  • Flusser J; Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.
Commun Eng ; 3(1): 140, 2024 Oct 09.
Article in En | MEDLINE | ID: mdl-39384858
ABSTRACT
Traditional image processing-based autofocusing techniques require the acquisition, storage, and processing of large amounts of image sequences, constraining focusing speed and cost. Here we propose an autofocusing technique, which directly and exactly acquires the geometric moments of the target object in real time at different locations by means of a proper image modulation and detection by a single-pixel detector. An autofocusing criterion is then formulated using the central moments, and the fast acquisition of the focal point is achieved by searching for the position that minimizes the criterion. Theoretical analysis and experimental validation of the method are performed and the results show that the method can achieve fast and accurate autofocusing. The proposed method requires only three single-pixel detections for each focusing position of the target object to evaluate the focusing criterion without imaging the target object. The method does not require any active object-to-camera distance measurement. Comparing to local differential methods such as contrast or gradient measurement, our method is more stable to noise and requires very little data compared with the traditional image processing methods. It may find a wide range of potential applications and prospects, particularly in low-light imaging and near-infra imaging, where the level of noise is typically high.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Commun Eng Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Commun Eng Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom