摘要
数字图像技术实现自动对焦的关键步骤是有效的图像清晰度评价。针对传统的灰度梯度算法抗噪性差和实时性低的问题,提出一种改进的清晰度评价算法。首先通过OSTU方法和全局方差计算出图像自适应分割阈值;然后比较自适应分割阈值和图像像素点局部方差以提取整幅图像中的边缘像素点;最后考虑人眼视觉特性,采用多方向的Tenengrad算子对图像进行评价运算,将图像中边缘像素点的评价运算值进行叠加,得到图像的清晰度量化值。为了衡量改进算法的性能,将其与传统的灰度梯度算法进行比较。实验结果表明,与传统的灰度梯度算法相比,所提算法具有实时性高、灵敏度强且抗噪能力好的优点。
The key step of digital image technology to realize autofocus is effective image sharpness evaluation.Aiming at the problems of poor anti-noise and low real-time performance of traditional gray gradient algorithms,an improved sharpness evaluation algorithm is proposed.First,the image adaptive segmentation threshold is calculated by the OSTU method and the global variance.Then,the adaptive segmentation threshold and the local variance of the image pixels are compared to extract the edge pixels in the entire image.Finally,considering the characteristics of human vision,the multi-direction Tenengrad operator is used to evaluate the image,and then the evaluation operation values of the edge pixels in the image are superimposed to obtain the quantized value of the image sharpness.In order to measure the performance of the improved algorithm,it is compared with the traditional gray gradient algorithm.The experimental results show that compared with the traditional gray gradient algorithm,the proposed algorithm has the advantages of high real-time performance,high sensitivity,and good anti-noise ability.
作者
曾海飞
韩昌佩
李凯
屠黄唯
Zeng Haifei;Han Changpei;Li Kai;Tu Huangwei(Shanghai lnstitute of Technical Physics,Chinese Academy of Sciences,Shanghai 200083,China;Key Laboratory of Ilnfrared Detection and Imaging Technology,Shanghai lnstitute of Technical Pihysics,Chinese Academy of Sciences,Shanghai 200083,China;University of Chinese Academgy of Sciences,Beijing 100049,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2021年第22期277-285,共9页
Laser & Optoelectronics Progress
基金
中国科学院上海技术物理研究所创新基金(CX-262)。
