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离焦模糊图像清晰度评价函数的分析与改进 总被引:2,自引:0,他引:2
传统的基于梯度的图像清晰度评价函数(调焦函数)对噪声敏感,在实际应用中易引入过多的非边缘信息,影响系统的稳定性。本文基于光学成像系统离焦模型分析了系统离焦对图像清晰度的影响,并提出了一种改进的图像清晰度评价方法。该方法利用最大灰度差提取细节信息来评价图像清晰度;引入阈值区分边缘点和非边缘点来减小图像平坦区域对评价函数灵敏度的影响,同时有效抑制噪声的干扰。进行了仿真实验和实际测试并与传统的清晰度评价函数进行了比较。结果显示,提出的方法具有更好的灵敏度和抗噪性能,能够准确而稳定地评价离焦模糊图像的清晰度,可用于实际光学系统的自动调焦。 相似文献
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在基因芯片荧光靶点阵列图像CCD扫描采集系统中,显微成像自动调焦控制是进行芯片杂交信号荧光靶点图像采集的先决条件.在定义图像清晰度评价函数的基础上,通过对实时采集的显微图像进行清晰度评价函数计算,采用基于粗精结合原则的自动调焦控制策略,实现了荧光靶点显微成像自动调焦控制.调焦控制实验表明,该方法显著提高了基因芯片荧光靶点图像聚焦和采集的效率. 相似文献
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基于图像处理的微装配自动调焦系统 总被引:7,自引:9,他引:7
介绍了一个基于图像处理的自动调焦系统,该系统由光学显微镜、CCD、力矩电机和齿轮传动机构等组成。调焦系统中采用粗/精结合的调焦方法,即首先采用基于Krisch边缘检测算子的清晰度评价函数对被测物体进行粗调焦,并在计算机上采集了包含目标的大致轮廓和边缘的显微图像;然后针对全景图像上的某个目标区域采用基于高频分量的清晰度评价函数进行精调焦,使得显微图像显示出更多的纹理细节。实验中清晰度评价函数算法均采用Windows下的Visual C++实现。实验结果表明,该自动调焦的系统精度可达±4.8 μm,基本上满足了微装配任务的调焦精度要求。 相似文献
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基于加权邻域相关性的显微镜自动聚焦函数 总被引:3,自引:1,他引:2
目的:提出了一种基于加权邻域相关性的显微镜自动聚焦函数,并在研究显微镜聚焦原理及成像过程的基础上,分析了显微镜图像中像素邻域灰度相关性及像散现象对聚焦评价的影响。方法:首先,分别计算每幅显微镜序列图像中各像素与其四邻域像素的灰度相关性。然后,计算基于此相关性加权平均值的二次多项式聚焦函数,其中权值根据对应像素与显微镜视场中心的距离来确定。最后,选取该函数值最大的图像为聚焦图像。结果:实验结果表明,与经典的聚焦函数如方差函数、绝对梯度函数、Roberts梯度函数及Tenengrad函数相比,本文方法的聚焦灵敏度因子提高了0.3185~0.3268,噪声环境下聚焦的平均正确率提高了0~40%。结论:该方法能够准确地评价图像聚焦的程度,并具有较高的灵敏度和较强的抗噪性。 相似文献
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图像调焦过程的清晰度评价函数研究 总被引:1,自引:0,他引:1
自动调焦是一类建立在搜索算法上的调焦方法,它通过计算机编程对不同对焦位置所成像的清晰度进行评价,利用正确对焦时图像最清晰这个特征找到正确的对焦位置。判断图像对焦与否是通过图像清晰度对焦评价函数/调焦状态评价函数(调焦判定函数)来衡量的。利用每一个调焦判定函数对包含了一组模糊和清晰图像的序列图像进行处理,可以得到对应于相应判定函数的调焦曲线,利用曲线可以非常直观地分析判定函数的性能。结果表明,灰度梯度函数具有比较稳定的调焦特性。 相似文献
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显微视觉系统的自动聚焦及控制 总被引:4,自引:0,他引:4
对自动显微镜的自动聚焦评价函数及聚焦控制策略进行了研究.首先,介绍了频域聚焦函数提升小波变换及时域聚焦函数Sobel-Tenengrad算子,通过将提升小波变换和Sobel-Tenengrad算子有机组合提出了一种新型聚焦评价函数.然后,利用离焦、正焦样本图像对自组织算法进行无监督训练,使用粒子群优化算法加速训练过程,并以经过学习的自组织映射算法作为聚焦控制器.最后,进行了显微视觉自动聚焦实验.实验结果表明:新型组合算子具有单峰性,峰值处变化陡峭,对不同样本、不同倍数物镜均可在正焦位置达到最大值,鲁棒性强;经过学习控制器后平均仅用7.6步即可完成自动聚焦,与爬山法相比,该聚焦算法不仅大大提高了聚焦速度且性能稳定,对每幅输入图像处理、识别时间约为120ms;满足了显微视觉自动聚焦要求,获得了良好聚焦效果. 相似文献
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考虑显微光学涉及的聚焦精度对机器视觉精密测量效果的影响,开展了显微视觉环境下对图像聚焦技术综合定量评价的研究。建立了偏移率等系列性能指标,对13组清晰度函数在显微视觉条件下的无偏性、单峰性、分辨力等进行了综合评价,优选出方差函数和Brenner函数分别用于粗聚焦和精聚焦阶段的清晰度计算。建立了分步爬山搜索法,实现了显微自动聚焦。与传统爬山法相比,提出的方法聚焦时间显著缩短,重复精度提高约24%。将建立的自动聚焦与图像测量方法应用于某电液伺服阀衔铁气隙测量中,得到的测量均值与工具显微镜结果相近,而测量标准差可达1.9μm,测量效率也显著提高。最后对伺服阀加电条件下的气隙动力学特性进行了测试,获得了驱动电流-衔铁气隙之间的关系,为在线装配/装调提供了重要依据。 相似文献
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Microscopy imaging can not achieve both high resolution and wide image space simultaneously. Autofocusing is of fundamental importance to automated micromanipulation. This article proposes a new wavelet-based focus measure, which is defined as a ratio of high frequency coefficients and low frequency coefficients. 8 series of 49 microscope images each acquired under five magnifications are used to comprehensively compare the performance of our focus measure with the classic and popular focus measures, including Normalized Variance, Entropy, Energy Laplace and wavelet-based high frequency focus measures. The robustness of these focus measures is evaluated using noisy image sequences corrupted by Gaussian white noise with standard deviations (STD) 5 and 15. An evaluation methodology is proposed, based on which these 5 focus measures are ranked. Experimental results show that the proposed focus measure can provide significantly the best overall performance and robustness. This focus measure can be widely applied to the automated biological and biomedical applications. 相似文献
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Zuojun Tan Dehui Sun Jing Xie Lu Chen Liang Li 《Microscopy research and technique》2014,77(4):289-295
Autofocusing technology is indispensable for routine use of microscopes on a large scale in biological field. The autofocusing method using the angle of Hilbert space is brought forward to measure whether the image is focused or not. The angle of Hillbert space can be used to evaluate accurately the similarity degree of two images. The experiment results show that the autofocusing method can decrease the computational cost and get accuracy for real‐time biological and biomedical images with noise robustness. The focus curves are smooth and possess the unimodality, the monotonicity and the symmetry. Compared with other classic and optimum focus method, the Hilbert method demonstrates its robustness to noise and can improve the focus speed. The experiments showed that the proposed method can increase the overall performance of an autofocus system and has strong applicability in various autofocusing algorithms. Microsc. Res. Tech. 77:289–295, 2014. © 2014 Wiley Periodicals, Inc. 相似文献
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显微镜自动粗调焦的TennenGrad改进算法 总被引:7,自引:0,他引:7
提出了使用Sobel算子或Laplace算子做卷积,对图像像素点进行绝对值相加的TennenGrad改进算法,以及Laplace改进算法,和几种已有评价函数进行分析比较。为了判断粗调评价函数的优劣,对评价函数的判断准则进行了逐一分析,并且将平滑性、高效率、强壮性作为最主要的衡量标准。在搭建的显微镜粗调实验系统中,对较为复杂的MEMS器件-微加速度计进行粗调成像。另外,对显微成像系统的调焦策略进行分析研究,提出并比较分析了3种调焦策略,其中n点灰度比较策略是较优的策略。实验处理结果表明,改进的TennenGrad算法具有最优的粗调特性,调焦范围较大,达到了210 μm;调焦分辨率高,达到7 μm,同时调焦图像显示出曲线变得更加平滑,曲线部极值点由5个减为0个。 相似文献
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Autofocusing is a fundamental technology for automated biological and biomedical analyses and is indispensable for routine use of microscopes on a large scale. This article presents a comprehensive comparison study of 18 focus algorithms in which a total of 139,000 microscope images were analyzed. Six samples were used with three observation methods (brightfield, phase contrast, and differential interference contrast (DIC)) under two magnifications (100x and 400x). A ranking methodology is proposed, based on which the 18 focus algorithms are ranked. Image preprocessing was also conducted to extensively reveal the performance and robustness of the focus algorithms. The presented guidelines allow for the selection of the optimal focus algorithm for different microscopy applications. 相似文献
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Prosper Oyibo Tope Agbana Lisette van Lieshout Wellington Oyibo Jan-Carel Diehl Gleb Vdovine 《Journal of microscopy》2024,294(1):52-61
Traditionally, automated slide scanning involves capturing a rectangular grid of field-of-view (FoV) images which can be stitched together to create whole slide images, while the autofocusing algorithm captures a focal stack of images to determine the best in-focus image. However, these methods can be time-consuming due to the need for X-, Y- and Z-axis movements of the digital microscope while capturing multiple FoV images. In this paper, we propose a solution to minimise these redundancies by presenting an optimal procedure for automated slide scanning of circular membrane filters on a glass slide. We achieve this by following an optimal path in the sample plane, ensuring that only FoVs overlapping the filter membrane are captured. To capture the best in-focus FoV image, we utilise a hill-climbing approach that tracks the peak of the mean of Gaussian gradient of the captured FoVs images along the Z-axis. We implemented this procedure to optimise the efficiency of the Schistoscope, an automated digital microscope developed to diagnose urogenital schistosomiasis by imaging Schistosoma haematobium eggs on 13 or 25 mm membrane filters. Our improved method reduces the automated slide scanning time by 63.18% and 72.52% for the respective filter sizes. This advancement greatly supports the practicality of the Schistoscope in large-scale schistosomiasis monitoring and evaluation programs in endemic regions. This will save time, resources and also accelerate generation of data that is critical in achieving the targets for schistosomiasis elimination. 相似文献
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Autofocusing (AF) criterion functions are critical to the performance of a passive autofocusing system in automatic video microscopy. Most of the autofocusing criterion functions proposed are dependent on the imaging system and image captured by the objective being focused or ranged. This dependence destabilizes the performance of the system when the criterion functions are applied to objectives with different characteristics. In this paper, a new design method for autofocusing criterion functions is introduced. This method enables the system to have the ability to tell the texture directional information of the objective. Based on this information, the optimal focus criterion function specific to one texture direction is designed, voiding blindly using autofocusing functions which cannot perform well when applied to the certain surface and can even lead to failure of the whole process. In this way, we improved the self-adaptability, robustness, reliability and focusing accuracy of the algorithm. First, the grey-level co-occurrence matrices of real-time images are calculated in four directions. Next, the contrast values of the four matrices are computed and then compared. The result reflects the directional information of the measured objective surfaces. Finally, with the directional information, an adaptive criterion function is constructed. To demonstrate the effectiveness of the new focus algorithm, we conducted experiments on different texture surfaces and compared the results with those obtained by existing algorithms. The proposed algorithm excellently performs with different measured objectives. 相似文献
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For the design of a passive autofocusing (AF) system for optical microscopes, many time‐consuming and tedious experiments have been performed to determine and design a better focus criterion function, owing to the sample‐dependence of this function. To accelerate the development of the AF systems in optical microscopes and to increase AF speed as well as maintain the AF accuracy, this study proposes a self‐adaptive and nonmechanical motion AF system. The presented AF system does not require the selection and design of a focus criterion function when it is developed. Instead, the system can automatically determine a better focus criterion function for an observed sample by analyzing the texture features of the sample and subsequently perform an AF procedure to bring the sample into focus in the objective of an optical microscope. In addition, to increase the AF speed, the Z axis scanning of the mechanical motion of the sample or the objective is replaced by focusing scanning performed by a liquid lens, which is driven by an electrical current and does not involve mechanical motion. Experiments show that the reproducibility of the results obtained with the proposed self‐adaptive and nonmechanical motion AF system is better than that provided by that of traditional AF systems, and that the AF speed is 10 times faster than that of traditional AF systems. Also, the self‐adaptive function increased the speed of AF process by an average of 10.5% than Laplacian and Tenegrad functions. 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