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

Tian Yingzhong; Cui Haoyang; Pan Zhiyan; Liu Jiaorong; Yang Shouchen; Liu Lilan; Wang Wenbin; Li Long

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

机译：基于非小波微波变换的多孔微观图像序列改进了三维重建算法

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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

机译：在多焦点微观图像测量方法中，三维（3D）重建模型的失真始终是影响测量结果的重要因素。在空间域中，焦点测量算法基于像素点的梯度变化，以确定像素的焦点。因此，难以准确地提取颜色差异不明显的区域中像素的焦点，从而导致3D模型失真。根据光学原理，清晰图像的高频系数大于模糊图像的高频系数。基于该特性，本文提出了一种新的多聚焦微观图像3D重建算法，使用非凹面的小波变换（NSWT）。 NSWT不考虑小波分解中的下采样，并具有平移的不变性。因此，可以在图像中计算每个像素的小波变换值，因此可以获得每个像素的高频系数;然后，在固定窗口中的像素点的高频系数上执行卷积计算，作为像素点的焦点测量值。与传统算法相比，本文提出的算法可以在聚焦测量曲线上表现出更好的单向和抗邻人性能。在本文中，实验对象的重建是阿里奇纳标准块三角和半圆形。所提出的算法和传统综合措施算法使用根均方误差，峰值信号到噪声比，以及与测量指标的相关系数。实验结果和比较分析证明了所提出的算法的正确性，并使基于多聚焦微观图像的3D模型进行更准确地重建。（c）2018年光学学会

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来源
《Applied optics》 |2018年第14期|共9页
作者
Tian Yingzhong; Cui Haoyang; Pan Zhiyan; Liu Jiaorong; Yang Shouchen; Liu Lilan; Wang Wenbin; Li Long;
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作者单位

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

Shenzhen Polytech Mech &

Elect Engn Sch Shenzhen 518055 Peoples R China;

Shanghai Univ Sch Mechatron Engn &

Automat Shanghai 200072 Peoples R China;

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

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