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Shape from focus (SFF) is a widely used passive optical method for 3D shape reconstruction. In SFF, a focus measure, which is used to estimate the relative focus level, plays a critical role in depth estimation. In this article, we present a new focus measure for accurate 3D shape estimation in optical microscopy based on the analysis of 3D structure tensor. First, the 3D tensors are computed from the input image sequence for each pixel. Then, each tensor is decomposed into point, curve, and surface tensors by decomposing tensors into eigenvalues and eigenvectors. Finally, the surfaceness is used to measure the quality of sharpness. The proposed focus measure provides accurate focus values and better resistance against noise. The proposed measure is evaluated by conducting experiments using image sequences of simulated and microscopic real objects. The comparative analysis demonstrates the effectiveness of the proposed focus measure in recovering 3D shape. 相似文献
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In this article, we introduce a novel shape from focus method to compute 3D shape of microscopic objects, based on modified‐pixel intensities and Bezier surface approximations. A new and simple but effective focus measure is proposed. In our focus measure, the original intensities of a sequence of small neighborhood are modified by subtracting the maximum of the values of first and last frames. An initial depth map is calculated by finding the maximum of the pixel's focused energy and its corresponding frame number. Missing information between two consecutive frames, false depth detection, and enhancement of noise related intensities may provide inaccurate depth map. To overcome these problems and to produce an accurate depth map, we proposed Bezier surface approximation. The proposed method is tested using synthetic and real image sequences. The comparative analysis demonstrates the effectiveness of the proposed method. Microsc. Res. Tech., 2010. © 2009 Wiley‐Liss, Inc. 相似文献
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Seong-O Shim 《Microscopy research and technique》2022,85(3):940-947
Shape from focus (SFF) is a technique to recover the shape of an object from multiple images taken at various focus settings. Most of conventional SFF techniques compute focus value of a pixel by applying one of focus measure operators on neighboring pixels on the same image frame. However, in the optics with limited depth of field, neighboring pixels of an image have different degree of focus for curved objects, thus the computed focus value does not reflect the accurate focus level of the pixel. Ideally, an accurate focus value of a pixel needs to be measured from the neighboring pixels lying on tangential plane of the pixel in image space. In this article, a tangential plane on each pixel location (i, j) in image sensor is searched by selecting one of five candidate planes based on the assumption that the maximum variance of focus values along the optical axis is achieved from the neighborhood lying on tangential plane of the pixel (i, j). Then, a focus measure operator is applied on neighboring pixels lying on the searched plane. The experimental results on both the synthetic and real microscopic objects show the proposed method produces more accurate three-dimensional shape in comparison to conventional SFF method that applies focus measures on original image planes. 相似文献
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Muhammad Tariq Mahmood 《Microscopy research and technique》2014,77(12):959-963
In this letter, a shape from focus (SFF) method is proposed that utilizes the guided image filtering to enhance the image focus volume efficiently. First, image focus volume is computed using a conventional focus measure. Then each layer of image focus volume is filtered using guided filtering. In this work, the all‐in‐focus image, which can be obtained from the initial focus volume, is used as guidance image. Finally, improved depth map is obtained from the filtered image focus volume by maximizing the focus measure along the optical axis. The proposed SFF method is efficient and provides better depth maps. The improved performance is highlighted by conducting several experiments using image sequences of simulated and real microscopic objects. The comparative analysis demonstrates the effectiveness of the proposed SFF method. Microsc. Res. Tech. 77:959–963, 2014. © 2014 Wiley Periodicals, Inc. 相似文献
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This article introduces a new algorithm for shape from focus (SFF) based on discrete cosine transform (DCT) and principal component analysis (PCA). DCT is applied on a small 3D neighborhood for each pixel in the image volume. Instead of summing all focus values in a window, AC parts of DCT are collected and then PCA is applied to transform this data into eigenspace. The first feature, containing maximum variation is employed to compute the depth. DCT and PCA are computationally intensive; however, the reduced data elements and algorithm iterations have made the new approach competitive and efficient. The performance of the proposed approach is compared with other methods by conducting experiments using image sequences of a synthetic and two microscopic objects. The evaluation is gauged on the basis of unimodality, monotonicity, and resolution of the focus curve. Two other global statistical metrics, root mean square error (RMSE) and correlation have also been applied for synthetic image sequence. Besides, noise sensitivity and computational complexity are also compared with other algorithms. Experimental results demonstrate the effectiveness and the robustness of the new method. 相似文献
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The logarithmic image processing (LIP) model is a mathematical framework which provides algebraic and functional operations for the processing of intensity images valued in a bounded range. The LIP model has been proved to be physically consistent, most notably with some image formation models and several laws and characteristics of human brightness perception. This paper addresses the image focus measurement problem using the LIP model. The three most classical image focus measurements: the sum-modified-Laplacian, the tenengrad and the variance, which aim at estimating the degree of focus of an acquired image by emphasizing and quantifying its sharpness information, are considered and reinterpreted using the LIP framework. These reinterpretations notably make attempts at evaluating degrees of focus in terms of human brightness (sensation) from physical light stimuli. Their potential is illustrated and validated on shape-from-focus issues on both simulated data and real acquisitions in digital optical microscopy. The concept of shape-from-focus involves recovering the shape of an observed thick sample by locally maximizing a focus measurement throughout a sequence of differently focused images. Finally, it is shown that the LIP-based focus measurements clearly outperform their respective classical ones. 相似文献
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Abdul Majid Muhammad Tariq Mahmood Tae‐Sun Choi 《Microscopy research and technique》2010,73(7):657-661
Generally, in shape from focus techniques, a single focus measure is used in estimating the three‐dimensional structure of microscopic objects. However, the performance of a single focus measure is limited to estimate accurately the depth map of diverse type of objects. To cope with this problem, we propose genetic programming based novel approach by developing an optimal composite depth (OCD) function for accurate depth estimation. This OCD function optimally combines the initial depth and focus information extracted from individual focus measures. An improved performance of this function is reported for synthetic and real world microscopic objects. Microsc. Res. Tech., 2010. © 2010 Wiley‐Liss, Inc. 相似文献
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利用衍射光学元件增加出射光束的焦深 总被引：1，自引：1，他引：0
在入射光束的孔径受限制的情况下,利用衍射光学元件来增加激光束的焦深。首先确定光阑孔径的大小、然后利用Y-G算法,在已知入射和出射光波函数的条件下,计算出衍射光学元件的位相分布。计算结果表明焦深可以比未用衍射光学元件时增加一半或更多。 相似文献
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Optical microscopy allows a magnified view of the sample while decreasing the depth of focus. Although the acquired images from limited depth of field have both blurred and focused regions, they can provide depth information. The technique to estimate the depth and 3D shape of an object from the images of the same sample obtained at different focus settings is called shape from focus (SFF). In SFF, the measure of focus–sharpness–is the crucial part for final 3D shape estimation. The conventional methods compute sharpness by applying focus measure operator on each 2D image frame of the image sequence. However, such methods do not reflect the accurate focus levels in an image because the focus levels for curved objects require information from neighboring pixels in the adjacent frames too. To address this issue, we propose a new method based on focus adjustment which takes the values of the neighboring pixels from the adjacent image frames that have approximately the same initial depth as of the center pixel and then it re-adjusts the center value accordingly. Experiments were conducted on synthetic and microscopic objects, and the results show that the proposed technique generates better shape and takes less computation time in comparison with previous SFF methods based on focused image surface (FIS) and dynamic programming. Microsc. Res. Tech., 2009. © 2008 Wiley-Liss, Inc. 相似文献
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In this article, we propose a new shape from focus (SFF) method to estimate 3D shape of microscopic objects using surface orientation cue of each object patch. Most of the SFF algorithms compute the focus value of a pixel from the information of neighboring pixels lying on the same image frame based on an assumption that the small object patch corresponding to the small neighborhood of a pixel is a plane parallel to the focal plane. However, this assumption fails in the optics with limited depth of field where the neighboring pixels of an image have different degree of focus. To overcome this problem, we try to search the surface orientation of the small object patch corresponding to each pixel in the image sequence. Searching of the surface orientation is done indirectly by principal component analysis. Then, the focus value of each pixel is computed from the neighboring pixels lying on the surface perpendicular to the corresponding surface orientation. Experimental results on synthetic and real microscopic objects show that the proposed method produces more accurate 3D shape in comparison to the existing techniques. 相似文献
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In nature, objects have partially weak texture and their shape reconstruction using focus based passive methods like shape from focus (SFF), is difficult. This article presents a new SFF algorithm which can compute precise depth of dense as well as weak textured objects. Segmentation is applied to discard wrong depth estimate and then later interpolating them from accurate depth values of their neighbors. The performance of the proposed method is tested, using different image sequences of synthetic and real objects, with varying textures. Microsc. Res. Tech., 2009. © 2009 Wiley‐Liss, Inc. 相似文献
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The methods of image deconvolution are important for improving the quality of the detected images in the different modalities of fluorescence microscopy such as wide‐field, confocal, two‐photon excitation and 4Pi. Because deconvolution is an ill‐posed problem, it is, in general, reformulated in a statistical framework such as maximum likelihood or Bayes and reduced to the minimization of a suitable functional, more precisely, to a constrained minimization, because non‐negativity of the solution is an important requirement. Next, iterative methods are designed for approximating such a solution. In this paper, we consider the Bayesian approach based on the assumption that the noise is dominated by photon counting, so the likelihood is of the Poisson‐type, and that the prior is edge‐preserving, as derived from a simple Markov random field model. By considering the negative logarithm of the a posteriori probability distribution, the computation of the maximum a posteriori (MAP) estimate is reduced to the constrained minimization of a functional that is the sum of the Csiszár I‐divergence and a regularization term. For the solution of this problem, we propose an iterative algorithm derived from a general approach known as split‐gradient method (SGM) and based on a suitable decomposition of the gradient of the functional into a negative and positive part. The result is a simple modification of the standard Richardson–Lucy algorithm, very easily implementable and assuring automatically the non‐negativity of the iterates. Next, we apply this method to the particular case of confocal microscopy for investigating the effect of several edge‐preserving priors proposed in the literature using both synthetic and real confocal images. The quality of the restoration is estimated both by computation of the Kullback–Leibler divergence of the restored image from the detected one and by visual inspection. It is observed that the noise artefacts are considerably reduced and desired characteristics (edges and minute features as islets) are retained in the restored images. The algorithm is stable, robust and tolerant at various noise (Poisson) levels. Finally, by remarking that the proposed method is essentially a scaled gradient method, a possible modification of the algorithm is briefly discussed in view of obtaining fast convergence and reduction in computational time. 相似文献
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聚焦深度法广泛地应用于小尺寸零构件的三维形貌测量。 针对聚焦评价曲线多存在噪声导致三维形貌测量的精度下降,且效率受图像序列数目和聚焦评价算法限制的难题,通过结合双拟合优化理论与聚焦单峰性评价指标提出了一种基于自适应权重的聚焦极值搜寻方法,并进一步基于三次多项式二次插值算法和多级中值混合滤波优化深度信息。 实验结果表明,方法对仿真图像数据的均方根误差(RMSE)较高斯拟合和多项式拟合分别降低了 19. 08% 、17. 32% , 对球栅阵列封装 (BGA) 图像中受噪声干扰较大的区域仍具三维分辨能力,同时对钻削刀具进行了测量,提出的方法在 50% 的图像序列数目和图像分辨下RMSE 仍降低了 77. 8% 、62. 6% ,有效减少了聚焦曲线噪声对测量结果影响的同时提升了三维测量的效率。 相似文献
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Cefalì E Patanè S Arena A Saitta G Guglielmino S Cappello S Nicolò M Allegrini M 《Scanning》2002,24(6):274-283
The morphologic and structural variations suffered by cells of a population of Pseudomonas aeruginosa ATCC 27853 under stress conditions were investigated by using scanning near-field optical microscopy. The analysis of the images, supported by microbiological data, showed that the bacteria evolved from the initial distribution of rod-shaped cells of standard size to a population with structural and morphologic modifications. The detection of variations in the optical reflectivity over a subwavelength scale (< or = 100 nm), combined with the concurrently acquired topographical signal, allowed the visualisation of rod-shaped bacteria going towards a lytic process and entire \"U\"-shaped cells. In the latter cells, which derived from a morphology refolding of rod bacteria, cellular matter seemed to rearrange itself to attain a coccoid stress resistant form, responsible for the residual viability of the population. 相似文献