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A fast auto-focusing method of microscopic imaging based on an improved MCS algorithm

Journal of Innovative Optical Health Sciences 2015年第5期8卷 67-76页

作者： Guangkai Fu Yiping Cao Mingteng Lu Department of Optical Electronics Sichuan University Chengdu 610064P.R.China

An improved"three steps"mountain-climb searching(MCS)algorithm is proposed which is applied to auto-focusing for microscopic imaging accurately and *** analyzing the performance of several evaluation functions,the variance function and the Brenner function are synthesized as a new evaluation *** the first step,a self-adaptive step length which is much dependent on the reciprocal of the evaluation function value at the beginning position of climbing is used for approaching the halfway up the mountain ***,a fixed moderate step length is applied for approaching the mountaintop of the variance function as closer as ***,afine step is employed for reaching the exact mountaintop of the Brenner *** microscope auto-focusing experiments based on the proposed algorithm for blood smear detection have been carried out *** results show that the improved algorithm can not only guarantee the precision to get clear focal images,but also improve the auto-focusing e±ciency.

关键词： auto-focusing evaluation function mountain-climb searching algorithm image processing

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An auto-focusing Method Based on Image Processing Technique

An Auto-focusing Method Based on Image Processing Technique

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第三届国际仪器科学技术学术研讨会

作者： CUI Ji-wen TAN Jiu-bin Institute of Ultra-precision Optoelectronic Instrument Engineering Harbin Institute of Technology Harbin 150001 China

In order to improve the image processing precision and the performance of system, an auto-focusing method based on image processing technique is proposed. An improved grayscale difference function was

关键词： auto-focusing Improved grayscale difference function homomorphic filtering variable step searching

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An auto-focus algorithm for imaging of objects under a lossy earth from multi-frequency and multi-monostatic data

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Science China(Information Sciences) 2010年第9期53卷 1880-1890页

作者： LIU YanLi1,2,LI LianLin1 & LI Fang1* 1Institute of Electronics,Chinese Academy of Sciences,Beijing 100190,China 2National Science Library,Chinese Academy of Sciences,Beijing 100049,China Institute of Electronics Chinese Academy of Sciences Beijing China National Science Library Chinese Academy of Sciences Beijing China

The problem of auto-focusing imaging of 2D dielectric objects imbedded in a lossy earth is *** Born approximation,the half-space spectrum Green's function is employed to formulate the half-space imaging algorithm from multi-frequency and multi-monostatic *** the fast Fourier transform can be used to achieve real-time imaging in a very short computing *** the proposed algorithm has avoided the time-consuming regularization of a large-scale ill-posed matrix,the computing time can be greatly cut *** by the principle of time reversed imaging and the minimum entropy criterion,an auto-focusing imaging algorithm is presented to remove the image degradation caused by estimated error of the unknown dielectric parameters of the *** results have shown that the proposed algorithm can provide good quality focused images for both low-contrast and high-contrast targets in a short computing time despite the inaccurate estimation of the earth electric *** proposed algorithm can be extended to three-dimensional case naturally.

关键词： multi-frequency multi-monostatic minimum entropy auto-focusing lossy earth time reversal imaging(TRI)

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Efficiency Analysis of the autofocusing Algorithm Based on Orthogonal Transforms

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Journal of Computer and Communications 2013年第6期1卷 41-45页

作者： Przemyslaw Sliwinski Krzysztof Berezowski Piotr Patronik Pawel Wachel Institute of Computer Engineering Control and RoboticsWroclaw University of TechnologyWroclawPoland

Efficiency of the autofocusing algorithm implementations based on various orthogonal transforms is examined. The algorithm uses the variance of an image acquired by a sensor as a focus function. To compute the estimate of the variance we exploit the equivalence between that estimate and the image orthogonal expansion. Energy consumption of three implementations exploiting either of the following fast orthogonal transforms: the discrete cosine, the Walsh-Hadamard, and the Haar wavelet one, is evaluated and compared. Furthermore, it is conjectured that the computation precision can considerably be reduced if the image is heavily corrupted by the noise, and a simple problem of optimal word bit-length selection with respect to the signal variance is analyzed.

关键词： auto-focusing Image Variance Discrete Orthogonal Transforms Word-Length Selection Architectural Performance Evaluation

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