中国科技核心期刊

中文核心期刊

CSCD来源期刊

空间控制技术与应用 ›› 2025, Vol. 51 ›› Issue (1): 43-53.doi: 10.3969/j.issn.1674 1579.2025.01.005

• 论文与报告 • 上一篇    下一篇

结合多区域窗口的梯度阈值清晰度评价方法

  

  1. 北京控制工程研究所
  • 出版日期:2025-02-26 发布日期:2025-03-06
  • 基金资助:
    国家自然科学基金资助项目(52405247)

The Method of Gradient Thresholds Sharpness Evaluating Combined Multi Region Window

  • Online:2025-02-26 Published:2025-03-06

摘要: 针对传统清晰度评价方法存在曲线平坦、多峰甚至误判的问题,提出一种结合多区域窗口的梯度阈值清晰度评价方法.利用梯度图像的对比度和加权方差计算分割阈值,提取图像的边缘点,对边缘点采用改进的能量梯度函数得到区域图像的清晰度评价结果,对不同区域图像的评价值赋予不同的权重,得到整幅图像的评价结果.本文方法与传统方法进行对比,结果表明采用同一评价函数时,多区域窗口相较于传统窗口,评价曲线单峰、无误判.本文方法灵敏度因子比传统方法的最优结果平均提升55.6%,陡峭度平均提升58.3%,该方法可为空间光学传感器自动调焦应用提供有效的参考依据.

关键词: 自动调焦, 图像处理, 清晰度评价, 调焦窗口

Abstract: To address the issues of flat curves, multi peaks, and misjudgments in traditional sharpness evaluation methods, a gradient threshold based sharpness evaluation method combining multiple region windows is proposed. The method utilizes the contrast and weighted variance of the gradient image to calculate a segmentation threshold and extract edge points. An improved energy gradient function is then applied to evaluate the sharpness of the region image at the edge points. Different weights are assigned to the evaluation values of various regions to obtain the final evaluation result for the entire image. Comparing this method with traditional approaches, the results show that when using the same evaluation function, the multi region window produces a unimodal evaluation curve without misjudgments, in contrast to the traditional window. The sensitivity factor of this method is, on average, 55.6% higher, and the steepness is 58.3% higher than the optimal results from traditional methods. Therefore, the proposed method can provide an effective reference for automatic focusing applications in space optical sensors.

Key words: autofocus, image processing, sharpness evaluation, focusing window

中图分类号: 

  • V44