The Experts below are selected from a list of 5247 Experts worldwide ranked by ideXlab platform
Olaf Ronneberger - One of the best experts on this subject based on the ideXlab platform.
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Variational attenuation correction in two-view confocal microscopy
BMC bioinformatics, 2013Co-Authors: Thorsten Schmidt, Jasmin Dürr, Margret Keuper, Thomas Blein, Klaus Palme, Olaf RonnebergerAbstract:Background Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the Underdetermined Problem of estimating the attenuation-free intensities.
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Variational attenuation correction in two-view confocal microscopy
BMC Bioinformatics, 2013Co-Authors: Thorsten Schmidt, Jasmin Dürr, Margret Keuper, Thomas Blein, Klaus Palme, Olaf RonnebergerAbstract:Background Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the Underdetermined Problem of estimating the attenuation-free intensities. Results We present a variational approach to estimate both, the real intensities and the spatially variant attenuation from two views of the same sample from opposite sides. Assuming noise-free measurements throughout the whole volume and pure absorption, this would in theory allow a perfect reconstruction without further assumptions. To cope with real world data, our approach respects photon noise, estimates apparent bleaching between the two recordings, and constrains the attenuation field to be smooth and sparse to avoid spurious attenuation estimates in regions lacking valid measurements. Conclusions We quantify the reconstruction quality on simulated data and compare it to the state-of-the art two-view approach and commonly used one-factor-per-slice approaches like the exponential decay model. Additionally we show its real-world applicability on model organisms from zoology (zebrafish) and botany (Arabidopsis). The results from these experiments show that the proposed approach improves the quantification of confocal microscopic data of thick specimen.
Hualou Liang - One of the best experts on this subject based on the ideXlab platform.
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A blind source separation based method for speech encryption
IEEE Transactions on Circuits and Systems I: Regular Papers, 2006Co-Authors: Qiu-hua Lin, Fuliang Yin, Tie-min Mei, Hualou LiangAbstract:The Underdetermined Problem poses a significant challenge in blind source separation (BSS) where the number of the source signals is greater than that of the mixed signals. Motivated by the fact that the security of many cryptosystems relies on the apparent intractability of the computational Problems such as the integer factorization Problem, we exploit the intractability of the Underdetermined BSS Problem to present a novel BSS-based speech encryption by properly constructing the Underdetermined mixing matrix for encryption, and by generating the key signals that satisfy the necessary condition for the proposed method to be unconditionally secure. Both extensive computer simulations and performance analyses results show that the proposed method has high level of security while retaining excellent audio quality
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ISNN (2) - Blind source separation-based encryption of images and speeches
Advances in Neural Networks – ISNN 2005, 2005Co-Authors: Qiu-hua Lin, Fuliang Yin, Hualou LiangAbstract:Blind source separation (BSS) has been successfully applied in many fields such as communications and biomedical engineering. Its application for image and speech encryption, however, has been scarce. Motivated by the fact that the security of many public-key cryptosystems relies on the apparent intractability of the computational Problems such as the integer factorization Problem, we present a BSS-based method for encrypting images and speeches by utilizing the BSS Underdetermined Problem. We discuss how to construct the mixing matrix for encryption and how to generate the key signals. Computer simulation results show that the BSS-based method has high level of security.
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Blind source separation-based encryption of images and speeches
Lecture Notes in Computer Science, 2005Co-Authors: Qiu-hua Lin, Fuliang Yin, Hualou LiangAbstract:Blind source separation (BSS) has been successfully applied in many fields such as communications and biomedical engineering. Its application for image and speech encryption, however, has been scarce. Motivated by the fact that the security of many public-key cryptosystems relies on the apparent intractability of the computational Problems such as the integer factorization Problem, we present a BSS-based method for encrypting images and speeches by utilizing the BSS Underdetermined Problem. We discuss how to construct the mixing matrix for encryption and how to generate the key signals. Computer simulation results show that the BSS-based method has high level of security.
Huaqing Wang - One of the best experts on this subject based on the ideXlab platform.
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Underdetermined blind source separation with variational mode decomposition for compound roller bearing fault signals
Sensors, 2016Co-Authors: Gang Tang, Weihua Zhang, Caijin Yang, Huaqing WangAbstract:In the condition monitoring of roller bearings, the measured signals are often compounded due to the unknown multi-vibration sources and complex transfer paths. Moreover, the sensors are limited in particular locations and numbers. Thus, this is a Problem of Underdetermined blind source separation for the vibration sources estimation, which makes it difficult to extract fault features exactly by ordinary methods in running tests. To improve the effectiveness of compound fault diagnosis in roller bearings, the present paper proposes a new method to solve the Underdetermined Problem and to extract fault features based on variational mode decomposition. In order to surmount the shortcomings of inadequate signals collected through limited sensors, a vibration signal is firstly decomposed into a number of band-limited intrinsic mode functions by variational mode decomposition. Then, the demodulated signal with the Hilbert transform of these multi-channel functions is used as the input matrix for independent component analysis. Finally, the compound faults are separated effectively by carrying out independent component analysis, which enables the fault features to be extracted more easily and identified more clearly. Experimental results validate the effectiveness of the proposed method in compound fault separation, and a comparison experiment shows that the proposed method has higher adaptability and practicability in separating strong noise signals than the commonly-used ensemble empirical mode decomposition method.
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diagnosis of roller bearings compound fault using Underdetermined blind source separation algorithm based on null space pursuit
Shock and Vibration, 2015Co-Authors: Chunguang Wu, Huaqing WangAbstract:In order to solve the Problem of Underdetermined blind source separation (BSS) in the diagnosis of compound fault of roller bearings, an Underdetermined BSS algorithm based on null-space pursuit (NSP) was proposed. In this algorithm, the signal model of faulty roller bearing is firstly used to construct an appropriate differential operator in null space. With the constructed differential operator, the mixed signals collected by the vibration sensor are decomposed into a series of stacks of narrow band signal containing the characteristics of faulty bearing. Finally, the Underdetermined Problem is transformed to an overdetermined Problem by combining the narrow band signals and the original mixed signals into a new group of observed signals. In this way, the separation of the mixed signals can be realized. Experiments and engineering data analyses show that the Problem of Underdetermined BSS can be solved effectively by this approach, and then the compound fault of the roller bearing can be separated.
Thorsten Schmidt - One of the best experts on this subject based on the ideXlab platform.
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Variational attenuation correction in two-view confocal microscopy
BMC bioinformatics, 2013Co-Authors: Thorsten Schmidt, Jasmin Dürr, Margret Keuper, Thomas Blein, Klaus Palme, Olaf RonnebergerAbstract:Background Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the Underdetermined Problem of estimating the attenuation-free intensities.
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Variational attenuation correction in two-view confocal microscopy
BMC Bioinformatics, 2013Co-Authors: Thorsten Schmidt, Jasmin Dürr, Margret Keuper, Thomas Blein, Klaus Palme, Olaf RonnebergerAbstract:Background Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the Underdetermined Problem of estimating the attenuation-free intensities. Results We present a variational approach to estimate both, the real intensities and the spatially variant attenuation from two views of the same sample from opposite sides. Assuming noise-free measurements throughout the whole volume and pure absorption, this would in theory allow a perfect reconstruction without further assumptions. To cope with real world data, our approach respects photon noise, estimates apparent bleaching between the two recordings, and constrains the attenuation field to be smooth and sparse to avoid spurious attenuation estimates in regions lacking valid measurements. Conclusions We quantify the reconstruction quality on simulated data and compare it to the state-of-the art two-view approach and commonly used one-factor-per-slice approaches like the exponential decay model. Additionally we show its real-world applicability on model organisms from zoology (zebrafish) and botany (Arabidopsis). The results from these experiments show that the proposed approach improves the quantification of confocal microscopic data of thick specimen.
Qiu-hua Lin - One of the best experts on this subject based on the ideXlab platform.
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A blind source separation based method for speech encryption
IEEE Transactions on Circuits and Systems I: Regular Papers, 2006Co-Authors: Qiu-hua Lin, Fuliang Yin, Tie-min Mei, Hualou LiangAbstract:The Underdetermined Problem poses a significant challenge in blind source separation (BSS) where the number of the source signals is greater than that of the mixed signals. Motivated by the fact that the security of many cryptosystems relies on the apparent intractability of the computational Problems such as the integer factorization Problem, we exploit the intractability of the Underdetermined BSS Problem to present a novel BSS-based speech encryption by properly constructing the Underdetermined mixing matrix for encryption, and by generating the key signals that satisfy the necessary condition for the proposed method to be unconditionally secure. Both extensive computer simulations and performance analyses results show that the proposed method has high level of security while retaining excellent audio quality
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ISNN (2) - Blind source separation-based encryption of images and speeches
Advances in Neural Networks – ISNN 2005, 2005Co-Authors: Qiu-hua Lin, Fuliang Yin, Hualou LiangAbstract:Blind source separation (BSS) has been successfully applied in many fields such as communications and biomedical engineering. Its application for image and speech encryption, however, has been scarce. Motivated by the fact that the security of many public-key cryptosystems relies on the apparent intractability of the computational Problems such as the integer factorization Problem, we present a BSS-based method for encrypting images and speeches by utilizing the BSS Underdetermined Problem. We discuss how to construct the mixing matrix for encryption and how to generate the key signals. Computer simulation results show that the BSS-based method has high level of security.
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Blind source separation-based encryption of images and speeches
Lecture Notes in Computer Science, 2005Co-Authors: Qiu-hua Lin, Fuliang Yin, Hualou LiangAbstract:Blind source separation (BSS) has been successfully applied in many fields such as communications and biomedical engineering. Its application for image and speech encryption, however, has been scarce. Motivated by the fact that the security of many public-key cryptosystems relies on the apparent intractability of the computational Problems such as the integer factorization Problem, we present a BSS-based method for encrypting images and speeches by utilizing the BSS Underdetermined Problem. We discuss how to construct the mixing matrix for encryption and how to generate the key signals. Computer simulation results show that the BSS-based method has high level of security.
