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图像清晰度评价与变步长融合调焦方法
引用本文:潘宏亮,孙金霞,韩希珍. 图像清晰度评价与变步长融合调焦方法[J]. 红外与激光工程, 2023, 52(1): 20220342-1-20220342-6. DOI: 10.3788/IRLA20220342
作者姓名:潘宏亮  孙金霞  韩希珍
作者单位:1.长春精仪光电技术有限公司 研发部,吉林 长春 130000
基金项目:吉林省科技发展计划项目(20200401009GX)
摘    要:十字丝目标在CCD上的成像,一般受到环境光和光路的影响,不同位置的焦距产生的十字丝图像会存在边缘模糊和离焦的情况,使十字目标的中心点位置提取受到严重影响,传统的Sobel算法忽视边缘信息,并且容易受噪声影响,因此提出改进Sobel算子图像清晰度评价函数与粗细调焦结合的变步长两段式快速搜索自动调焦的方法。该方法首先利用图像的空间域评价图像清晰度,其次利用根据光学设计选用的两段式调焦方式。第一步进行粗调,先快速找到正焦位置附近,然后进行细调,直至找到正焦的位置。实验表明,该方法与其他算法相比,自动调焦失败率为2%,调焦时间为1 242 ms,调焦行程在-25~+30 mm之间。通过该算法将图像清晰度评价函数与两段式调焦方式结合进行自动调焦,准确性高,实时性好。

关 键 词:自动调焦  清晰度评价函数  变步长  空间域  光学设计
收稿时间:2022-05-18

Image sharpness evaluation and variable-step fusion focusing method
Affiliation:1.Research and Development Department, Changchun Jingyi Photoelectric Technology Co., Ltd., Changchun 130000, China2.Research and Development Department, Suzhou Dongfang Kloto Photoelectric Technology Co., Ltd., Suzhou 215600, China
Abstract:The imaging of the cross wire target on the CCD is generally affected by the ambient light and the optical path. The cross wire image generated by the focal length of different positions will be blurred and out of focus, and the extraction of the center point of the cross wire target will be seriously affected. The traditional Sobel algorithm ignores the edge information and is easily affected by noise. Therefore, a two-stage fast search auto focusing method with variable-step size is proposed, which improves the image sharpness evaluation function of Sobel operator and combines the coarse and fine focusing. The method first evaluates the image sharpness by using the spatial domain of the image, and then selects the two-stage focusing mode according to the optical design. The first step is coarse adjustment. When the focus position is quickly found, fine adjustment is performed until the focus position is found. Experimental results show that compared with other algorithms, the auto focusing failure rate is 2%, the focusing time is 1242 ms, and the focusing stroke is ?25-30 mm. The combination of the image sharpness evaluation function and the two-stage focusing mode through this algorithm has high accuracy and good real-time performance.
Keywords:
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