Chen Huiling, Shi Dongfeng, Guo Zijun, Jiang Runbo, Zha Linbin, Wang Yingjian, Flusser Jan
School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, 230026, China.
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. 2024 Oct 9;3(1):140. doi: 10.1038/s44172-024-00288-z.
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.
基于传统图像处理的自动聚焦技术需要采集、存储和处理大量图像序列，这限制了聚焦速度和成本。在此，我们提出一种自动聚焦技术，该技术通过适当的图像调制并由单像素探测器进行检测，在不同位置实时直接且精确地获取目标物体的几何矩。然后利用中心矩制定自动聚焦准则，并通过搜索使该准则最小化的位置来实现焦点的快速获取。对该方法进行了理论分析和实验验证，结果表明该方法能够实现快速且精确的自动聚焦。对于目标物体的每个聚焦位置，所提出的方法仅需三次单像素检测即可评估聚焦准则，而无需对目标物体成像。该方法不需要任何主动的物距测量。与诸如对比度或梯度测量等局部差分方法相比，我们的方法对噪声更稳定，并且与传统图像处理方法相比所需的数据非常少。它可能会有广泛的潜在应用和前景，特别是在噪声水平通常较高的低光成像和近红外成像中。
