Jang Hoon-Seok, Yun Guhnoo, Mutahira Husna, Muhammad Mannan Saeed
IT Application Research Center, Jeonbuk Regional Branch, Korea Electronics Technology Institute, Jeonju, Republic of Korea.
Center for Intelligent and Interactive Robotics, Korea Institute of Science and Technology, Seoul, Republic of Korea.
Microsc Res Tech. 2021 Oct;84(10):2483-2493. doi: 10.1002/jemt.23781. Epub 2021 Apr 27.
Measuring the image focus is an important issue in Shape from Focus methods. Conventionally, the Sum of Modified Laplacian, Gray Level Variance (GLV), and Tenengrad techniques have been used frequently among various focus measure operators for estimating the focus levels in a sequence of images. However, they have various issues such as fixed window size and suboptimal focus quality. To solve these problems, a new focus measure operator based on the adaptive sum of weighted modified Laplacian is proposed. First, the adaptive window size selection algorithm based on the GLV is applied. Next, appropriate weights are assigned to the Modified Laplacian values in the image window based on the distance between the center pixel and neighboring pixels. Finally, the Weighted Modified Laplacian values in the image window are summed. Experimental results demonstrate the effectiveness of the proposed method.
在基于聚焦形状的方法中，测量图像焦点是一个重要问题。传统上，在各种焦点测量算子中，修正拉普拉斯算子之和、灰度方差（GLV）和梯度幅值平方和技术经常被用于估计图像序列中的焦点水平。然而，它们存在诸如固定窗口大小和焦点质量次优等各种问题。为了解决这些问题，提出了一种基于加权修正拉普拉斯算子自适应和的新焦点测量算子。首先，应用基于GLV的自适应窗口大小选择算法。接下来，根据中心像素与相邻像素之间的距离，为图像窗口中的修正拉普拉斯值分配适当的权重。最后，对图像窗口中的加权修正拉普拉斯值求和。实验结果证明了该方法的有效性。
