Research And Application In Design Of Super-depth-of-field Microscope Of Focus Stacking Algorithm

As the human observation of the microscopic world demand,microscope is widely used.But traditional microscope in use process have inconvenience,such as slow focus,depth of field.Super-depth-of-field image fusion algorithm based on image sequence,is collected in the same scene but the focus is not clear,to obtain a global focus clear image.This algorithm can break the depth limit of traditional optical microscope,design a convenient and practical super-depth-of-field microscope.Super-depth-of-field microscopy at high magnification can clearly observe the thicker samples,is widely used in the field of medical,biology and industrial production.Therefore,this paper studied the multiple image fusion algorithm,such as Image fusion algorithm based on image pyramid,Image fusion algorithm based on wavelet transform and Image fusion algorithm based on optimization,and put forward a kind of high efficient extended-depth-of-field algorithm used in the design of super-depth-of-field microscope.First of all,the method proposed in this paper,through designing an adaptive focus measurement according to image texture and resolution,test the degree of focus in all position of all the images in the image sequence.In order to enhance the system robustness,according to the characteristics of the optical microscope,the focus measurement expressed with a Gaussian distribution,to simulate the depth information and focus of real scene.Then,in order to reduce the effects of noise and special samples for the fusion results and adapt to more and more application scenarios,the method in this paper each,will divide all pixels in the image into three types,according to the different focus measurement,and aims at different focusing characteristics using different fusion rules.In a nutshell,the fused image "matching" by the original image sequence through different weighted average or select check rules.Here,this step was called local weighted average fusion rule.In the region of the image which is clear and low noise,an image will be fused by only one image.And in the case of image region contains noise,an image will be fused by two of three images.In addition,the poor quality of information of the image area,the Fusion rule will be replace by the nearbydecision.Finally,in order to evaluate the effectiveness of the proposed algorithm,with a large number of simulation data and real data,the relevant experiment widely,in this paper.Finally the quantitative and qualitative results show the depth-of-field image fusion algorithm in this paper is simple and very effective.In addition,a large number of comparative quantitative analysis algorithm is proved algorithm is proposed in this paper both,in effect and speed is far superior to the traditional way.Later,this article respectively on the simulated data and real data has carried on the contrast experiment.Through the analysis of experimental results,the method was proved to be an effective depth-of-field image fusion algorithm.In addition,compared to the previous algorithm,the method in this paper have a big promotion in the computing speed,is also more efficient and practical in the process of practical application.Notable is,a use of the proposed algorithm over super-depth-of-field of digital optical microscope are actually designed and has been used in industry,show the results of real industrial samples to customer satisfaction,and won the large economic benefit.