4.5 Article

Improved three-dimensional reconstruction algorithm from a multifocus microscopic image sequence based on a nonsubsampled wavelet transform

期刊

APPLIED OPTICS
卷 57, 期 14, 页码 3864-3872

出版社

OPTICAL SOC AMER
DOI: 10.1364/AO.57.003864

关键词

-

类别

资金

  1. National Natural Science Foundation of China (NSFC) [91748122]
  2. National Science Foundation for Young Scientists of China [61603237]
  3. Shanghai Pujiang Program [17PJ1402900]
  4. Science and Technology Commission of Shanghai Municipality (STCSM) [16111107802, 16111108202]

向作者/读者索取更多资源

In the multifocus microscopic image measurement method, the distortion of the three-dimensional (3D) reconstruction model has always been an important factor affecting the measurement result. In spatial domains, the focus measure algorithm is based on the gradient change of the pixel point to determine the degree of focus of the pixel. So it will be difficult to accurately extract the focus of the pixel in the areas where color difference is not obvious, resulting in 3D model distortion. According to the optical principle, the high-frequency coefficients of the clear image are larger than the high-frequency coefficients of the blurred image. Based on this characteristic, this paper proposes a new multifocus microscopic image 3D reconstruction algorithm using a nonsubsampled wavelet transform (NSWT). The NSWT does not consider the downsampling in wavelet decomposition and has translational invariance. Therefore, the wavelet transform value of each pixel can be calculated in the image, so the high-frequency coefficient of each pixel can be obtained; then the convolution calculation is performed on the high-frequency coefficients of the pixel points in the fixed window as the focus measure value of the pixel point. Compared with the traditional algorithm, the algorithm proposed in this paper can show better unimodal and antinoise performance on the focusing measure curve. In this paper, the reconstruction of the experimental object is Alicona standard block triangular and semicylindrical. The proposed algorithm and the traditional algorithm for comprehensive measure use the root mean square error, peak signal to noise ratio, and correlation coefficient as the measure index. The experimental results and comparative analysis prove the correctness of the proposed algorithm and enable more accurate reconstruction of 3D models based on multifocus microscopic images. (C) 2018 Optical Society of America

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据