Pub Date : 2023-10-01DOI: 10.18287/2412-6179-co-1313
V.V. Ivakhnik, D.R. Kapizov, V.I. Nikonov
Spatial selectivity of six-wave radiation converters, which perform double wavefront conjugation of a signal wave in long multimode waveguides with both Kerr and thermal nonlinearities, is studied. Waveguides with infinitely conductive surfaces, with a parabolic refractive index profile, were used. It is shown that the spatial structure of the first pump wave does not affect the quality of doubled wavefront conjugation in a waveguide with Kerr nonlinearity, but only slightly affects the quality of doubled wavefront conjugation in a waveguide with thermal nonlinearity. A decrease in the radius of the second Gaussian pump wave on the back face of the waveguide leads to an improvement in the quality of the doubled wavefront reversal both in the case of six-wave interaction in the Kerr and thermal nonlinearities. In a parabolic waveguide, when the zero mode of the waveguide is excited by pump waves at a constant frequency of the second pump wave, an increase in the frequency of the first pump wave worsens the quality of the double wavefront conjugation.
{"title":"Six-wave interaction with double wavefront reversal in multimode waveguides with Kerr and thermal nonlinearities","authors":"V.V. Ivakhnik, D.R. Kapizov, V.I. Nikonov","doi":"10.18287/2412-6179-co-1313","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1313","url":null,"abstract":"Spatial selectivity of six-wave radiation converters, which perform double wavefront conjugation of a signal wave in long multimode waveguides with both Kerr and thermal nonlinearities, is studied. Waveguides with infinitely conductive surfaces, with a parabolic refractive index profile, were used. It is shown that the spatial structure of the first pump wave does not affect the quality of doubled wavefront conjugation in a waveguide with Kerr nonlinearity, but only slightly affects the quality of doubled wavefront conjugation in a waveguide with thermal nonlinearity. A decrease in the radius of the second Gaussian pump wave on the back face of the waveguide leads to an improvement in the quality of the doubled wavefront reversal both in the case of six-wave interaction in the Kerr and thermal nonlinearities. In a parabolic waveguide, when the zero mode of the waveguide is excited by pump waves at a constant frequency of the second pump wave, an increase in the frequency of the first pump wave worsens the quality of the double wavefront conjugation.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136056113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.18287/2412-6179-co-1314
D.V. Soshnikov, L.L. Doskolovich, E.V. Byzov
We consider a gradient method for calculating cascaded diffractive optical elements (DOEs) consisting of several sequentially placed phase DOEs. Using the unitarity property of the operator describing the light propagation through the cascaded DOE, we obtained explicit expressions for the derivatives of the error functional with the respect to the phase functions of the cascaded DOE. We consider the application of the gradient method in the problem of focusing several different incident beams to several domains with different intensity distributions, and in the problem of image classification. The presented description of the gradient method treats the problems of designing cascaded DOEs for both focusing the laser radiation and performing image classification in the framework of a single general approach. It is shown that the difference of the problem of optical classification from the problem of generating required intensity distributions consists only in the form of error functionals, the calculation of the derivatives of which is reduced to the same general formula. Using the proposed gradient method, we designed single and cascaded DOEs for optical classification of handwritten digits. The obtained results may find application in the development of diffractive neural networks and optical systems for laser beam focusing.
{"title":"Gradient method for designing cascaded DOEs and its application in the problem of classifying handwritten digits","authors":"D.V. Soshnikov, L.L. Doskolovich, E.V. Byzov","doi":"10.18287/2412-6179-co-1314","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1314","url":null,"abstract":"We consider a gradient method for calculating cascaded diffractive optical elements (DOEs) consisting of several sequentially placed phase DOEs. Using the unitarity property of the operator describing the light propagation through the cascaded DOE, we obtained explicit expressions for the derivatives of the error functional with the respect to the phase functions of the cascaded DOE. We consider the application of the gradient method in the problem of focusing several different incident beams to several domains with different intensity distributions, and in the problem of image classification. The presented description of the gradient method treats the problems of designing cascaded DOEs for both focusing the laser radiation and performing image classification in the framework of a single general approach. It is shown that the difference of the problem of optical classification from the problem of generating required intensity distributions consists only in the form of error functionals, the calculation of the derivatives of which is reduced to the same general formula. Using the proposed gradient method, we designed single and cascaded DOEs for optical classification of handwritten digits. The obtained results may find application in the development of diffractive neural networks and optical systems for laser beam focusing.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136056116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.18287/2412-6179-co-1274
S.I. Kharitonov, V.A. Fursov
We offer a computer technology for modeling a process of optical imaging with a diffractive imaging lens. The central idea of the technology is to evaluate the quality of the optical system by matching the input and output images against criteria adopted in image processing. For this purpose, same-resolution hyperspectral images are fed to the input and generated at the output. Thanks to the large number of spectral components, a fairly accurate reproduction of the effects associated with the dependence of the refractive index on the wavelength is ensured. To compare input and output images in terms of PSNR (peak signal-to-noise ratio), standard three-component RGB images are "assembled" using standard matching functions over the entire optical range. Results of the study of the dependence of the PSNR indicator on the main parameters of the optical system are given: focal length, linear aperture and the number of diffraction orders taken into account.
{"title":"Computer simulation of diffractive imaging lenses using hyperspectral images","authors":"S.I. Kharitonov, V.A. Fursov","doi":"10.18287/2412-6179-co-1274","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1274","url":null,"abstract":"We offer a computer technology for modeling a process of optical imaging with a diffractive imaging lens. The central idea of the technology is to evaluate the quality of the optical system by matching the input and output images against criteria adopted in image processing. For this purpose, same-resolution hyperspectral images are fed to the input and generated at the output. Thanks to the large number of spectral components, a fairly accurate reproduction of the effects associated with the dependence of the refractive index on the wavelength is ensured. To compare input and output images in terms of PSNR (peak signal-to-noise ratio), standard three-component RGB images are \"assembled\" using standard matching functions over the entire optical range. Results of the study of the dependence of the PSNR indicator on the main parameters of the optical system are given: focal length, linear aperture and the number of diffraction orders taken into account.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136056131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper presents main aspects of the application of artificial intelligence in ophthalmology for the diagnosis and treatment of eye diseases, considering the problem of semantic segmentation of fundus images as an example. The classic approach to semantic segmentation on the basis of textural features is compared to the proposed approach based on neural networks. Basic problems of using the neural network approach in biomedicine are formulated. We propose a new method for selecting an optimal zone of laser exposure for laser coagulation based on two neural networks. The first network is used for detecting anatomical objects in the fundus and the second one is used for selecting the area of macular edema. The region of interest is formed from the edema area while taking into account the location of anatomical objects in it. A comparative analysis of sev-eral architectures of neural networks for solving the problem of selecting the edema area is carried out. The best results in the selection of the edema area are shown by the neural network architecture of Unet++.
{"title":"Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images","authors":"N.S. Demin, N.Y. Ilyasova, R.A. Paringer, D.V. Kirsh","doi":"10.18287/2412-6179-co-1283","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1283","url":null,"abstract":"The paper presents main aspects of the application of artificial intelligence in ophthalmology for the diagnosis and treatment of eye diseases, considering the problem of semantic segmentation of fundus images as an example. The classic approach to semantic segmentation on the basis of textural features is compared to the proposed approach based on neural networks. Basic problems of using the neural network approach in biomedicine are formulated. We propose a new method for selecting an optimal zone of laser exposure for laser coagulation based on two neural networks. The first network is used for detecting anatomical objects in the fundus and the second one is used for selecting the area of macular edema. The region of interest is formed from the edema area while taking into account the location of anatomical objects in it. A comparative analysis of sev-eral architectures of neural networks for solving the problem of selecting the edema area is carried out. The best results in the selection of the edema area are shown by the neural network architecture of Unet++.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.18287/2412-6179-co-1345
L.A. Manilo, A.P. Nemirko
More and more attention is being paid to the development of methods for the objective analysis of biosignals for computer medical systems. The search for new non-standard methods is aimed at improving the reliability of diagnostics and expanding the areas of their practical application. In this paper, methods for recognizing biomedical signals by the degree of severity of their nonlinear components are considered. An approach based on the use of approximate entropy closely related to Kolmogorov entropy (K-entropy) is used. Its parameters can be used to detect dynamic irregularities associated with nonlinear properties of signals. The algorithm for calculating this characteristic is consid-ered in detail. Based on model experiments, its main properties are analyzed. It is shown that the entropy of a finite sequence, calculated in accordance with a multistep pro-cedure, can give an erroneous estimate of the degree of regularity of the signal. A procedure for correcting the approximate entropy is proposed, which expands the area of analysis of this function for estimating nonlinearity. It has been established that the transition to adjusted entropy makes it possible to increase the reliability of the detection of chaotic components. A set of entropy parameters is proposed for constructing recognition procedures. Examples of solving the problems of detecting atrial fibrillation by the parameters of the non-linearity of the rhythmogram, as well as assessing the depth of anesthesia by the electroencephalogram (EEG) are given. Experiments conducted on real recordings of electrocardiogram (ECG) and EEG signals have shown the high efficiency of the proposed algorithms. The proposed methods and algorithms can be used in the development of systems for monitoring ECG of cardiological patients, as well as monitoring the depth of anesthesia by EEG during surgical operations.
{"title":"Recognition of biosignals with nonlinear properties by approximate entropy parameters","authors":"L.A. Manilo, A.P. Nemirko","doi":"10.18287/2412-6179-co-1345","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1345","url":null,"abstract":"More and more attention is being paid to the development of methods for the objective analysis of biosignals for computer medical systems. The search for new non-standard methods is aimed at improving the reliability of diagnostics and expanding the areas of their practical application. In this paper, methods for recognizing biomedical signals by the degree of severity of their nonlinear components are considered. An approach based on the use of approximate entropy closely related to Kolmogorov entropy (K-entropy) is used. Its parameters can be used to detect dynamic irregularities associated with nonlinear properties of signals. The algorithm for calculating this characteristic is consid-ered in detail. Based on model experiments, its main properties are analyzed. It is shown that the entropy of a finite sequence, calculated in accordance with a multistep pro-cedure, can give an erroneous estimate of the degree of regularity of the signal. A procedure for correcting the approximate entropy is proposed, which expands the area of analysis of this function for estimating nonlinearity. It has been established that the transition to adjusted entropy makes it possible to increase the reliability of the detection of chaotic components. A set of entropy parameters is proposed for constructing recognition procedures. Examples of solving the problems of detecting atrial fibrillation by the parameters of the non-linearity of the rhythmogram, as well as assessing the depth of anesthesia by the electroencephalogram (EEG) are given. Experiments conducted on real recordings of electrocardiogram (ECG) and EEG signals have shown the high efficiency of the proposed algorithms. The proposed methods and algorithms can be used in the development of systems for monitoring ECG of cardiological patients, as well as monitoring the depth of anesthesia by EEG during surgical operations.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced microscopy technologies such as electron microscopy have opened up a new field of vision for biomedical researchers. The use of artificial intelligence methods for processing EM data is largely difficult due to the small amount of annotated data at the training stage. Therefore, we add synthetic images to an annotated real EM dataset or use a fully synthetic training dataset. In this work, we present an algorithm for the synthesis of 6 types of organelles. Based on the EPFL dataset, a training set of 1161 real fragments 256×256 (ORG) and 2000 synthetic ones (SYN), as well as their combination (MIX), were generated. The experiment of training models for 6, 5-classes and binary segmentation showed that, despite the imperfections of synthetics, training on a mixed (MIX) dataset gave a significant increase (about 0.1) in the Dice metric for 6 and 5 and same results at binary. The synthetic data strategy gives annotations for free, but shifts the effort to producing sufficiently realistic images.
{"title":"Generation and study of the synthetic brain electron microscopy dataset for segmentation purpose","authors":"N.A. Sokolov, E.P. Vasiliev, A.A. Getmanskaya","doi":"10.18287/-6179-co-1273","DOIUrl":"https://doi.org/10.18287/-6179-co-1273","url":null,"abstract":"Advanced microscopy technologies such as electron microscopy have opened up a new field of vision for biomedical researchers. The use of artificial intelligence methods for processing EM data is largely difficult due to the small amount of annotated data at the training stage. Therefore, we add synthetic images to an annotated real EM dataset or use a fully synthetic training dataset. In this work, we present an algorithm for the synthesis of 6 types of organelles. Based on the EPFL dataset, a training set of 1161 real fragments 256×256 (ORG) and 2000 synthetic ones (SYN), as well as their combination (MIX), were generated. The experiment of training models for 6, 5-classes and binary segmentation showed that, despite the imperfections of synthetics, training on a mixed (MIX) dataset gave a significant increase (about 0.1) in the Dice metric for 6 and 5 and same results at binary. The synthetic data strategy gives annotations for free, but shifts the effort to producing sufficiently realistic images.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136056115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.18287/2412-6179-co-1284
A.N. Galyntich, M.A. Raifeld
When there is no information about the number of brightness classes, synthesizing algorithms for automatic image threshold segmentation involves a problem of determining the number of thresholds. The solution to the problem of estimating the number of classes in an image can be based on representing its distribution as a mixture of distributions of brightness classes when priori probabilities are unknown, or estimating the number of histogram modes. At the same time, it is known that the mixture splitting problem has a solution only for certain types of distributions and the histogram modes are not always distinguishable. In the general case, when the distributions of brightness classes are unknown, there are difficulties in applying these methods. The article proposes a non-parametric approach to determining the number of classes that differ in average brightness, based on rank histograms and using the property of local spatial grouping of elements of each brightness class in the image.
{"title":"Nonparametric estimation of the number of classes with different average brightness in thermal images","authors":"A.N. Galyntich, M.A. Raifeld","doi":"10.18287/2412-6179-co-1284","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1284","url":null,"abstract":"When there is no information about the number of brightness classes, synthesizing algorithms for automatic image threshold segmentation involves a problem of determining the number of thresholds. The solution to the problem of estimating the number of classes in an image can be based on representing its distribution as a mixture of distributions of brightness classes when priori probabilities are unknown, or estimating the number of histogram modes. At the same time, it is known that the mixture splitting problem has a solution only for certain types of distributions and the histogram modes are not always distinguishable. In the general case, when the distributions of brightness classes are unknown, there are difficulties in applying these methods. The article proposes a non-parametric approach to determining the number of classes that differ in average brightness, based on rank histograms and using the property of local spatial grouping of elements of each brightness class in the image.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.18287/2412-6179-co-1257
R. Chang, Z.X. Mao, J. Hu, H.C. Bai, C.J. Zhou, Y. Yang, S. Gao
The unique plateau geographical features and variable weather of Yunnan, China make transmission lines in this region more susceptible to coverage and damage by various foreign bodies compared to flat areas. The mountainous terrain also presents great challenges for inspecting and removing such objects. In order to improve the efficiency and detection accuracy of foreign body inspection of transmission lines, we propose a multi-UAV collaborative system specifically designed for the geographical characteristics of Yunnan's transmission lines in this paper. Additionally, the image data of foreign bodies was augmented, and the YOLOv7 target detection model, which offers a more balanced trade-off between precision and speed, was adopted to improve the accuracy and speed of foreign body detection.
{"title":"Research on foreign body detection in transmission lines based on a multi-UAV cooperative system and YOLOv7","authors":"R. Chang, Z.X. Mao, J. Hu, H.C. Bai, C.J. Zhou, Y. Yang, S. Gao","doi":"10.18287/2412-6179-co-1257","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1257","url":null,"abstract":"The unique plateau geographical features and variable weather of Yunnan, China make transmission lines in this region more susceptible to coverage and damage by various foreign bodies compared to flat areas. The mountainous terrain also presents great challenges for inspecting and removing such objects. In order to improve the efficiency and detection accuracy of foreign body inspection of transmission lines, we propose a multi-UAV collaborative system specifically designed for the geographical characteristics of Yunnan's transmission lines in this paper. Additionally, the image data of foreign bodies was augmented, and the YOLOv7 target detection model, which offers a more balanced trade-off between precision and speed, was adopted to improve the accuracy and speed of foreign body detection.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.18287/2412-6179-co-1262
V.Y. Kolyuchkin, N.M. Kostylev, Y.S. Gulina
The article describes a methodology for performance evaluation of vision systems for remotely operated underwater vehicles. The methodology is based on a system approach and uses mathematical models of the aqueous medium where an optical signal propagates, the underwater object image registration system, and the mathematical model of the human visual system. The detection and recognition probabilities of underwater object image at a given registration range are used as performance evaluation indicators of underwater vision systems. The mathematical model of the aqueous medium developed by the authors allows quantitative evaluation of the influence of backscattering interference arising during objects illumination on the underwater vision system performance. The results of numerical experiments presented in the paper illustrate the possibility of using the proposed technique to optimize the underwater object image registration system parameters in order to achieve the required values of detection or recognition probabilities at the given ranges.
{"title":"Performance evaluation of underwater vision systems","authors":"V.Y. Kolyuchkin, N.M. Kostylev, Y.S. Gulina","doi":"10.18287/2412-6179-co-1262","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1262","url":null,"abstract":"The article describes a methodology for performance evaluation of vision systems for remotely operated underwater vehicles. The methodology is based on a system approach and uses mathematical models of the aqueous medium where an optical signal propagates, the underwater object image registration system, and the mathematical model of the human visual system. The detection and recognition probabilities of underwater object image at a given registration range are used as performance evaluation indicators of underwater vision systems. The mathematical model of the aqueous medium developed by the authors allows quantitative evaluation of the influence of backscattering interference arising during objects illumination on the underwater vision system performance. The results of numerical experiments presented in the paper illustrate the possibility of using the proposed technique to optimize the underwater object image registration system parameters in order to achieve the required values of detection or recognition probabilities at the given ranges.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We discuss a problem of reconstructing (sectioning) multilayer object images in observed images obtained by focusing the imaging system on each layer and containing spurious blurry images of neighboring layers. The blurring model used describes a physical process of incoherent light scattering in the Fresnel approximation with a priori unknown parameters of the point spread function. We propose a method of "Boundary separation" of sectioning, which combines the use of a physical blur model with modern methods of blur estimating and edge detection. The results of testing the "Boundary separation" method on the data of physical experiments with different-scale model multilayer objects are analyzed and compared with the existing methods for solving the optical sectioning problem. It is concluded that the method is most effective on multilayer objects with clearly defined boundaries, on which the method has demonstrated almost complete restoration of the desired layers.
{"title":"Method of multilayer object sectioning based on a light scattering model","authors":"S.D. Bazhitov, A.V. Larichev, A.V. Razgulin, T.E. Romanenko","doi":"10.18287/2412-6179-co-1266","DOIUrl":"https://doi.org/10.18287/2412-6179-co-1266","url":null,"abstract":"We discuss a problem of reconstructing (sectioning) multilayer object images in observed images obtained by focusing the imaging system on each layer and containing spurious blurry images of neighboring layers. The blurring model used describes a physical process of incoherent light scattering in the Fresnel approximation with a priori unknown parameters of the point spread function. We propose a method of \"Boundary separation\" of sectioning, which combines the use of a physical blur model with modern methods of blur estimating and edge detection. The results of testing the \"Boundary separation\" method on the data of physical experiments with different-scale model multilayer objects are analyzed and compared with the existing methods for solving the optical sectioning problem. It is concluded that the method is most effective on multilayer objects with clearly defined boundaries, on which the method has demonstrated almost complete restoration of the desired layers.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136056121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：