基于灰度共生矩阵的自动聚焦算法

焦萍; 姜威; 贲晛烨; 刘湜; 张健钊

光学技术, 2018, 44 (3): 273, 网络出版: 2018-06-09

基于灰度共生矩阵的自动聚焦算法

Auto-focusing algorithm based on gray level co-occurrence matrix

论文大纲

焦萍 ^*姜威贲晛烨刘湜张健钊

作者单位

山东大学信息科学与工程学院, 山东济南 250100

自动聚焦清晰度评价灰度共生矩阵对比度纹理特征 Auto-focusing definition evaluation gray level co-occurrence matrix contrast texture feature

摘要

为了快速而准确的进行聚焦, 提出一种基于灰度共生矩阵的自动聚焦评价算法。算法利用灰度共生矩阵提取图像的纹理, 以此矩阵的对比度作为图像的清晰度值; 为了提高算法的实时性, 在计算对比度时, 选取合适的阈值去掉矩阵对角线附近灰度差较小的元素, 减少算法的计算量。实验结果表明: 算法满足无偏性和单峰性, 具有较高的灵敏度和陡峭度, 聚焦性能较好, 对引入噪声的图像同样具有很好的聚焦性能。

Abstract

In order to focus quickly and accurately, a kind of auto-focusing evaluation algorithm based on gray level co-occurrence matrix is put forward. The algorithm uses the gray level co-occurrence matrix to extract the texture of the image, and the contrast of the matrix is used as the sharpness value of the image. In order to improve the real-time performance of the algorithm, an appropriate threshold is selected to remove the elements with smaller gray levels near the diagonal of the matrix when the contrast is calculating, thereby reducing the computational complexity of the algorithm. The experimental results show that the algorithm satisfies unbiasedness and unimodality, has high sensitivity and steepness, good focusing performance, and also has good focusing performance on the noise-introduced images.

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焦萍, 姜威, 贲晛烨, 刘湜, 张健钊. 基于灰度共生矩阵的自动聚焦算法[J]. 光学技术, 2018, 44(3): 273. JIAO Ping, JIANG Wei, BEN Xianye, LIU Shi, Zhang Jianzhao. Auto-focusing algorithm based on gray level co-occurrence matrix[J]. Optical Technique, 2018, 44(3): 273.

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