Pub Date : 2022-03-30DOI: 10.1109/dspa53304.2022.9790752
V. M. Artyushenko, V. I. Volovach
The issues associated with the influence of multiplicative (modulating) (otherwise amplitude distortions) and additive noises on the processed signal are considered. Statistical characteristics of the probability density function of instantaneous values of the signal under the influence of multiplicative (modulating) noise are considered. Expressions are obtained to determine the probability density function of the instantaneous values of the useful signal, as well as a mixture of the signal and additive noise under the action of multiplicative noise. It is shown that the obtained mathematical expressions make it possible to simulate the probability density function of the said mixture at an arbitrary distribution law of the envelope signal. The issues also associated with the analysis of statistical characteristics of the envelope of the mixture of non-Gaussian periodically non-stationary signal and additive noise in the case when the envelopes of elementary reflected signals are described by a Rayleigh distribution are considered. The expression to determine the joint probability density function of quadrature components of a signal reflected from an area of an extended object in the form of a two-dimensional normal distribution is obtained. It is shown that these components are correlated and are determined by non-Gaussian probability density functions with different variances of quadrature components and thus the sum signal does not satisfy the necessary stationarity conditions. The condition of the initial moment values of the signal is given under which the square of the processed signal is not time-dependent. The analysis showed that the statistical characteristics of the periodically non-stationary signal in the presence non-Gaussian noise are completely determined by the parameters characterizing the statistical properties of the signal and the influencing noise. It is shown that the statistical characteristic of non-Gaussian periodically non-stationary signal in the presence of non-Gaussian noise is completely determined by the parameters characterizing the statistical properties of the signal and the affecting noise.
{"title":"Definition of the Statistical Characteristics of the Signal under Influence of Additive and Multiplicative Noise","authors":"V. M. Artyushenko, V. I. Volovach","doi":"10.1109/dspa53304.2022.9790752","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790752","url":null,"abstract":"The issues associated with the influence of multiplicative (modulating) (otherwise amplitude distortions) and additive noises on the processed signal are considered. Statistical characteristics of the probability density function of instantaneous values of the signal under the influence of multiplicative (modulating) noise are considered. Expressions are obtained to determine the probability density function of the instantaneous values of the useful signal, as well as a mixture of the signal and additive noise under the action of multiplicative noise. It is shown that the obtained mathematical expressions make it possible to simulate the probability density function of the said mixture at an arbitrary distribution law of the envelope signal. The issues also associated with the analysis of statistical characteristics of the envelope of the mixture of non-Gaussian periodically non-stationary signal and additive noise in the case when the envelopes of elementary reflected signals are described by a Rayleigh distribution are considered. The expression to determine the joint probability density function of quadrature components of a signal reflected from an area of an extended object in the form of a two-dimensional normal distribution is obtained. It is shown that these components are correlated and are determined by non-Gaussian probability density functions with different variances of quadrature components and thus the sum signal does not satisfy the necessary stationarity conditions. The condition of the initial moment values of the signal is given under which the square of the processed signal is not time-dependent. The analysis showed that the statistical characteristics of the periodically non-stationary signal in the presence non-Gaussian noise are completely determined by the parameters characterizing the statistical properties of the signal and the influencing noise. It is shown that the statistical characteristic of non-Gaussian periodically non-stationary signal in the presence of non-Gaussian noise is completely determined by the parameters characterizing the statistical properties of the signal and the affecting noise.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131376706","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790765
N. Chilikhin, Elena Karpukhina, V. Kutuzov
The paper is devoted to development and integration of the dynamic method of bandwidth management in service (control) communication channels for non-stationary objects. Polar codes (PC) were chosen as a scheme to combat interference in communication channels. Firstly, polar codes allow us to achieve the asymptotically possible bandwidth of a binary channel without memory. Secondly, they have the opportunity to freely choose the required code distance within the framework of the Hamming metric. The Bhattacharyya distance (BD) is used to provide the second advantage. This is a universal mechanism for determining the weight of a matrix row in a common generating matrix for the subsequent allocation of the most “strong/significant” matrix rows and the construction of any code vectors. It is important to note that the paper does not use the classical scheme for determining the likelihood ratio logarithm (LLR) but a modified one. For this purpose, there are used properties of the erasing communication channel (a wide erasure interval), integer values of the likelihood ratio logarithm to minimize computational costs (leveling time delays) and the assumption that the scope of variation changes quasi-linearly in the case of mathematical expectation. The paper describes the switching modes and the mechanism of bandwidth management that is determined by the tasks facing the designer and the operator of the communication system. Simulation was performed on FPGA Xilinx Artix-7 XC7A100T.
{"title":"Dynamic Bandwidth Management and Information Protection in Service Channels of Non-Stationary Objects","authors":"N. Chilikhin, Elena Karpukhina, V. Kutuzov","doi":"10.1109/dspa53304.2022.9790765","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790765","url":null,"abstract":"The paper is devoted to development and integration of the dynamic method of bandwidth management in service (control) communication channels for non-stationary objects. Polar codes (PC) were chosen as a scheme to combat interference in communication channels. Firstly, polar codes allow us to achieve the asymptotically possible bandwidth of a binary channel without memory. Secondly, they have the opportunity to freely choose the required code distance within the framework of the Hamming metric. The Bhattacharyya distance (BD) is used to provide the second advantage. This is a universal mechanism for determining the weight of a matrix row in a common generating matrix for the subsequent allocation of the most “strong/significant” matrix rows and the construction of any code vectors. It is important to note that the paper does not use the classical scheme for determining the likelihood ratio logarithm (LLR) but a modified one. For this purpose, there are used properties of the erasing communication channel (a wide erasure interval), integer values of the likelihood ratio logarithm to minimize computational costs (leveling time delays) and the assumption that the scope of variation changes quasi-linearly in the case of mathematical expectation. The paper describes the switching modes and the mechanism of bandwidth management that is determined by the tasks facing the designer and the operator of the communication system. Simulation was performed on FPGA Xilinx Artix-7 XC7A100T.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127697718","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790746
V. Krylov, K. Tatmyshevskiy, A. Bogachev, Maksim Yudin
Solving the problems of applied deep-level transient spectroscopy is associated with the need to improve the measurement accuracy. This imposes increased requirements on the accuracy of sample temperature maintaining while using the frequency-temperature scanning method and digital processing of capacitance transient signals that are weak with respect to noise. This report proposes an iterative adaptive algorithm for digital processing of the converted capacitance transient signal as a function of the repetition rate of deep-level filling pulses. The algorithm uses a piecewise continuous approximation for the measured sample temperature behavior, followed by a digital correction of the frequency scan during the iteration. As a result, it is possible to increase the accuracy of the deep-level activation energy and the pre-exponential factor measurements approximately twofold.
{"title":"Iterative Adaptive Digital Processing of Semiconductor Barrier Structures Capacitance Transient Signals","authors":"V. Krylov, K. Tatmyshevskiy, A. Bogachev, Maksim Yudin","doi":"10.1109/dspa53304.2022.9790746","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790746","url":null,"abstract":"Solving the problems of applied deep-level transient spectroscopy is associated with the need to improve the measurement accuracy. This imposes increased requirements on the accuracy of sample temperature maintaining while using the frequency-temperature scanning method and digital processing of capacitance transient signals that are weak with respect to noise. This report proposes an iterative adaptive algorithm for digital processing of the converted capacitance transient signal as a function of the repetition rate of deep-level filling pulses. The algorithm uses a piecewise continuous approximation for the measured sample temperature behavior, followed by a digital correction of the frequency scan during the iteration. As a result, it is possible to increase the accuracy of the deep-level activation energy and the pre-exponential factor measurements approximately twofold.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"60 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114036898","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790748
M. Mishchenko, E. Malkin, A. Solodchuk, O. Lukovenkova
The paper describes hardware and software implementation of distributed system for recording, collecting and digital processing of broadband geophysical signals. The signals are recorded at observation points that are significantly remote (over 350 km) from data collection and processing point. Structure of the distributed system and its distinctive features are considered. The system consists of two spatially separated hardware and software parts. These are an autonomous part at a remote observation point and a stationary part. The system parts are connected to a single network by a mobile communication channel. The autonomous part records geophysical signals. Hardware and software of the stationary part provide digital filtering, pulse detection, identification and classification, time-frequency analysis and structural linguistic processing of registered signals.
{"title":"Distributed System for Recording, Collecting, and Digital Processing of Broadband Geophysical Signals","authors":"M. Mishchenko, E. Malkin, A. Solodchuk, O. Lukovenkova","doi":"10.1109/dspa53304.2022.9790748","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790748","url":null,"abstract":"The paper describes hardware and software implementation of distributed system for recording, collecting and digital processing of broadband geophysical signals. The signals are recorded at observation points that are significantly remote (over 350 km) from data collection and processing point. Structure of the distributed system and its distinctive features are considered. The system consists of two spatially separated hardware and software parts. These are an autonomous part at a remote observation point and a stationary part. The system parts are connected to a single network by a mobile communication channel. The autonomous part records geophysical signals. Hardware and software of the stationary part provide digital filtering, pulse detection, identification and classification, time-frequency analysis and structural linguistic processing of registered signals.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122133652","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790783
E. Kurbatova, N. Kharina, A. Zemtsov, Stepan Plyaskin
Biometric systems for contactless identification of a person by palm blood vessels have become widespread recently. The relevance is due to a combination of such factors as hygiene, higher degree of protection against counterfeit, and delicacy compared to other methods. Vein pattern recognition algorithm can be divided into two steps. The first step, pre-processing, is to detect the Region-of-Interest (ROI). The second step involves extracting singular points of the vein bed (feature extraction) and matching the vein pattern with the database templates (feature matching) which can be performed using various methods. The paper presents the study of several parametric methods for recognizing and matching the input image with the database templates - correlation calculation, calculation of singular points (descriptors) and calculation of perceptual hashes. The comparative analysis of the results was carried out according to the following criteria - evaluating the recognition quality, evaluating the processing speed, estimating the size of the database. We have revealed a significant advantage of the hash method in comparison with other parametric methods under study within the paper. The results will be of use for developers of authentication systems based on image analysis.
{"title":"Investigating Palm Vein Pattern Recognition Methods","authors":"E. Kurbatova, N. Kharina, A. Zemtsov, Stepan Plyaskin","doi":"10.1109/dspa53304.2022.9790783","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790783","url":null,"abstract":"Biometric systems for contactless identification of a person by palm blood vessels have become widespread recently. The relevance is due to a combination of such factors as hygiene, higher degree of protection against counterfeit, and delicacy compared to other methods. Vein pattern recognition algorithm can be divided into two steps. The first step, pre-processing, is to detect the Region-of-Interest (ROI). The second step involves extracting singular points of the vein bed (feature extraction) and matching the vein pattern with the database templates (feature matching) which can be performed using various methods. The paper presents the study of several parametric methods for recognizing and matching the input image with the database templates - correlation calculation, calculation of singular points (descriptors) and calculation of perceptual hashes. The comparative analysis of the results was carried out according to the following criteria - evaluating the recognition quality, evaluating the processing speed, estimating the size of the database. We have revealed a significant advantage of the hash method in comparison with other parametric methods under study within the paper. The results will be of use for developers of authentication systems based on image analysis.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129269987","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790761
N. V. Arapov, A. Burova
The issues related to the study of the problem of accuracy of digital signal processing are considered. The purpose of the study is to estimate the error of difference digital filtering. Research methods - mathematical and hardware-software modeling of digital filters on programmable logic integrated circuits. An estimate of the error of differential digital filtering with integer difference coefficients is proposed and presented. It is shown that digital methods of spectral analysis based on difference digital filters with integer coefficients are not accurate, but the selection of values of the order of difference digital filtering and the order of its difference ensures the discrete Fourier transform without multiplication operations. It is proposed to increase the accuracy of spectral analysis by increasing these orders of magnitude, since the degree of approximation to the desired level of accuracy is determined by the permissible level of hardware costs for the computational algorithm of the method used.
{"title":"Accuracy of Spectral Analysis Based on Difference Digital Filtering","authors":"N. V. Arapov, A. Burova","doi":"10.1109/dspa53304.2022.9790761","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790761","url":null,"abstract":"The issues related to the study of the problem of accuracy of digital signal processing are considered. The purpose of the study is to estimate the error of difference digital filtering. Research methods - mathematical and hardware-software modeling of digital filters on programmable logic integrated circuits. An estimate of the error of differential digital filtering with integer difference coefficients is proposed and presented. It is shown that digital methods of spectral analysis based on difference digital filters with integer coefficients are not accurate, but the selection of values of the order of difference digital filtering and the order of its difference ensures the discrete Fourier transform without multiplication operations. It is proposed to increase the accuracy of spectral analysis by increasing these orders of magnitude, since the degree of approximation to the desired level of accuracy is determined by the permissible level of hardware costs for the computational algorithm of the method used.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133580391","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790774
V. Djigan
This paper presents two adaptive filters with a reduced arithmetic complexity which are based on the Recursive Least Squares (RLS) algorithms. The first one is the cascaded adaptive filter. The second one is the adaptive filter with the diagonalized correlation matrix of the input signal. The both filters have a reduced arithmetic complexity comparing to the direct implementation of the adaptive filter. The cost of the reduction is some degradation of the adaptive filter performance. The reduction is achieved only if the RLS algorithms with quadratic complexity are used. The computational procedures and the arithmetic complexities of the considered adaptive filters are the same, but the performance is different. This paper presents the RLS algorithms based on the Matrix Inversion Lemma (MIL). However, all the results and conclusions are valid for any RLS algorithms with quadratic complexity. The paper demonstrates the considered adaptive filter performance via simulation.
{"title":"Low Complexity RLS Adaptive Filters","authors":"V. Djigan","doi":"10.1109/dspa53304.2022.9790774","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790774","url":null,"abstract":"This paper presents two adaptive filters with a reduced arithmetic complexity which are based on the Recursive Least Squares (RLS) algorithms. The first one is the cascaded adaptive filter. The second one is the adaptive filter with the diagonalized correlation matrix of the input signal. The both filters have a reduced arithmetic complexity comparing to the direct implementation of the adaptive filter. The cost of the reduction is some degradation of the adaptive filter performance. The reduction is achieved only if the RLS algorithms with quadratic complexity are used. The computational procedures and the arithmetic complexities of the considered adaptive filters are the same, but the performance is different. This paper presents the RLS algorithms based on the Matrix Inversion Lemma (MIL). However, all the results and conclusions are valid for any RLS algorithms with quadratic complexity. The paper demonstrates the considered adaptive filter performance via simulation.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131016041","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790775
I. Lvovich, Ya.Ye. Lvovich, A. Preobrazhenskiy, Y. Preobrazhenskiy
The paper considers the problem associated with the construction of an antenna, based on the flat focusing reflector with waveguide slots of a square profile, filled with a homogeneous dielectric. Algorithms for antenna modeling and optimization are presented. Optimization is based on the use of a multi-criteria approach. The antenna directional diagram for the main frequency is demonstrated. Frequency dependences of antenna efficiency and aperture efficiency are shown. The illustration of the phase distribution that will correspond to the surface of the aperture for boundary frequencies is demonstrated. The illustration is given of the phase distribution at the emitting aperture at frequency for cutoff frequencies.
{"title":"Modeling the Characteristics of Antenna Based on the Flat Focusing Reflector","authors":"I. Lvovich, Ya.Ye. Lvovich, A. Preobrazhenskiy, Y. Preobrazhenskiy","doi":"10.1109/dspa53304.2022.9790775","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790775","url":null,"abstract":"The paper considers the problem associated with the construction of an antenna, based on the flat focusing reflector with waveguide slots of a square profile, filled with a homogeneous dielectric. Algorithms for antenna modeling and optimization are presented. Optimization is based on the use of a multi-criteria approach. The antenna directional diagram for the main frequency is demonstrated. Frequency dependences of antenna efficiency and aperture efficiency are shown. The illustration of the phase distribution that will correspond to the surface of the aperture for boundary frequencies is demonstrated. The illustration is given of the phase distribution at the emitting aperture at frequency for cutoff frequencies.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134089452","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 : 2022-03-30DOI: 10.1109/dspa53304.2022.9790755
O. S. Amosov, S. G. Amosova
This paper presents the method for automatic recognition of defects in aircraft riveted joints. The proposed method consists of three steps: pre-processing, feature extraction and classification. Feature extraction was then performed using discrete wavelet transform. Classification was performed using deep neural network. An example of solving the problem of detecting and recognizing a defect in rivets is considered.
{"title":"Method for Automatic Recognition of Defects in Aircraft Riveted Joints Using Wavelet Transform and Neural Network","authors":"O. S. Amosov, S. G. Amosova","doi":"10.1109/dspa53304.2022.9790755","DOIUrl":"https://doi.org/10.1109/dspa53304.2022.9790755","url":null,"abstract":"This paper presents the method for automatic recognition of defects in aircraft riveted joints. The proposed method consists of three steps: pre-processing, feature extraction and classification. Feature extraction was then performed using discrete wavelet transform. Classification was performed using deep neural network. An example of solving the problem of detecting and recognizing a defect in rivets is considered.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133160662","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 : 2022-03-30DOI: 10.1109/DSPA53304.2022.9805456
R. Kovalenko, A. Tashlinskii
This article investigates the influence of histogram intervals number on the accuracy and speed of the stochastic algorithm needed to solve the image alignment problem. The mutual information of images is considered as a similarity measure. Histograms are used for approximation of brightness probability density distributions when finding the gradient of image mutual information. Experimental results are obtained for the Shannon, Renyi and Tsallis mutual information cases.
{"title":"Optimization of the Histogram Intervals Number which Approximate Brightness Probability Distributions in Stochastic Image Alignment Based on Information Similarity Measures","authors":"R. Kovalenko, A. Tashlinskii","doi":"10.1109/DSPA53304.2022.9805456","DOIUrl":"https://doi.org/10.1109/DSPA53304.2022.9805456","url":null,"abstract":"This article investigates the influence of histogram intervals number on the accuracy and speed of the stochastic algorithm needed to solve the image alignment problem. The mutual information of images is considered as a similarity measure. Histograms are used for approximation of brightness probability density distributions when finding the gradient of image mutual information. Experimental results are obtained for the Shannon, Renyi and Tsallis mutual information cases.","PeriodicalId":428492,"journal":{"name":"2022 24th International Conference on Digital Signal Processing and its Applications (DSPA)","volume":"08 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127468057","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}
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