Covert communication guarantees the security of wireless communications via hiding the existence of the transmission.This paper focuses on the first and second order asymptotics of covert communication in the AWGN cha...Covert communication guarantees the security of wireless communications via hiding the existence of the transmission.This paper focuses on the first and second order asymptotics of covert communication in the AWGN channels.The covertness is measured by the total variation distance between the channel output distributions induced with and without the transmission.We provide the exact expressions of the maximum amount of information that can be transmitted with the maximum error probability and the total variation less than any small numbers.The energy detection and the random coding are employed to prove our results.We further compare our results with those under relative entropy.The results show how many additional amounts of information can be transmitted covertly when changing the covertness constraint to total variation.展开更多
For addressing impulse noise in images, this paper proposes a denoising algorithm for non-convex impulse noise images based on the l_(0) norm fidelity term. Since the total variation of the l_(0) norm has a better den...For addressing impulse noise in images, this paper proposes a denoising algorithm for non-convex impulse noise images based on the l_(0) norm fidelity term. Since the total variation of the l_(0) norm has a better denoising effect on the pulse noise, it is chosen as the model fidelity term, and the overlapping group sparse term combined with non-convex higher term is used as the regularization term of the model to protect the image edge texture and suppress the staircase effect. At the same time, the alternating direction method of multipliers, the majorization–minimization method and the mathematical program with equilibrium constraints were used to solve the model. Experimental results show that the proposed model can effectively suppress the staircase effect in smooth regions, protect the image edge details, and perform better in terms of the peak signal-to-noise ratio and the structural similarity index measure.展开更多
In this paper, we propose a novel shear gradient operator by combining the shear and gradient operators. The shear gradient operator performs well to capture diverse directional information in the image gradient domai...In this paper, we propose a novel shear gradient operator by combining the shear and gradient operators. The shear gradient operator performs well to capture diverse directional information in the image gradient domain. Based on the shear gradient operator, we extend the total variation(TV) norm to the shear total variation(STV) norm by adding two shear gradient terms. Subsequently, we introduce a shear total variation deblurring model. Experimental results are provided to validate the ability of the STV norm to capture the detailed information. Leveraging the Block Circulant with Circulant Blocks(BCCB) structure of the shear gradient matrices, the alternating direction method of multipliers(ADMM) algorithm can be used to solve the proposed model efficiently. Numerous experiments are presented to verify the performance of our algorithm for non-blind image deblurring.展开更多
A new method for reconstructing the compressed sensing color image by solving an optimization problem based on total variation in the quaternion field is proposed, which can effectively improve the reconstructing abil...A new method for reconstructing the compressed sensing color image by solving an optimization problem based on total variation in the quaternion field is proposed, which can effectively improve the reconstructing ability of the color image. First, the color image is converted from RGB （red, green, blue） space to CMYK （cyan, magenta, yellow, black） space, which is assigned to a quaternion matrix. Meanwhile, the quaternion matrix is converted into the information of the phase and amplitude by the Euler form of the quatemion. Secondly, the phase and amplitude of the quatemion matrix are used as the smoothness constraints for the compressed sensing （CS） problem to make the reconstructing results more accurate. Finally, an iterative method based on gradient is used to solve the CS problem. Experimental results show that by considering the information of the phase and amplitude, the proposed method can achieve better performance than the existing method that treats the three components of the color image as independent parts.展开更多
This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorizati...This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorization by total variation constraint and graph regularization.The main contributions of our work are the following.First,total variation is incorporated into NMF to control the diffusion speed.The purpose is to denoise in smooth regions and preserve features or details of the data in edge regions by using a diffusion coefficient based on gradient information.Second,we add graph regularization into NMF to reveal intrinsic geometry and structure information of features to enhance the discrimination power.Third,the multiplicative update rules and proof of convergence of the TV-GNMF algorithm are given.Experiments conducted on datasets show that the proposed TV-GNMF method outperforms other state-of-the-art algorithms.展开更多
In foggy weather, images of outdoor scene are usually characterized with poor visibility as well as faint color saturation. The degraded hazy images may have substantial negative impact on most computer vision systems...In foggy weather, images of outdoor scene are usually characterized with poor visibility as well as faint color saturation. The degraded hazy images may have substantial negative impact on most computer vision systems. Thus image haze removal is of the practical significance in engineering. This paper proposes a fast and effective single image haze removal algorithm on the basis of the physics imaging model. To extract the global atmospheric light accurately, we exploit multiple prior rules underlying hazy images, and put forward a novel measurement to judge the likelihood that a pixel is regarded as the global atmospheric light. In addition, the rough transmission map is estimated through a multiscale fusion process based on the Laplace pyramid transform, and refined by a total variation model. Experimental results demonstrate the proposed method outperforms most of the state-of-the-art algorithms in terms of the dehazing quality, and achieves a trade-off between the computational efficiency and haze removal capability.展开更多
In this paper,we propose a discrepancy rule-based method to automatically choose the regularization parameters for total variation image restoration problems. The regularization parameters are adjusted dynamically in ...In this paper,we propose a discrepancy rule-based method to automatically choose the regularization parameters for total variation image restoration problems. The regularization parameters are adjusted dynamically in each iteration.Numerical results are shown to illustrate the performance of the proposed method.展开更多
In this paper,we propose a new image denoising method that combines total variation(TV)method and wavelet shrinkage.In our method,a noisy image is decomposed into subbands of LL,LH,HL,and HH in wavelet domain.LL subba...In this paper,we propose a new image denoising method that combines total variation(TV)method and wavelet shrinkage.In our method,a noisy image is decomposed into subbands of LL,LH,HL,and HH in wavelet domain.LL subband contains the low frequency coefficients along with less noise,which can be easily eliminated using TV-based method.More edges and other detailed information like textures are contained in the other three subbands,and we propose a shrinkage method based on the local variance to extract them from high frequency noise.Experimental results show that this method retains the edges and textures very well while removing noise.展开更多
Directionality of image plays a very important role in human visual system and it is important prior information of image. In this paper we propose a weighted directional total variation model to reconstruct image fro...Directionality of image plays a very important role in human visual system and it is important prior information of image. In this paper we propose a weighted directional total variation model to reconstruct image from its finite number of noisy compressive samples. A novel self-adaption, texture preservation method is designed to select the weight. Inspired by majorization-minimization scheme, we develop an efficient algorithm to seek the optimal solution of the proposed model by minimizing a sequence of quadratic surrogate penalties. The numerical examples are performed to compare its performance with four state-of-the-art algorithms. Experimental results clearly show that our method has better reconstruction accuracy on texture images than the existing scheme.展开更多
Abstract This paper aims at the multichannel synthetic aperture radar （SAR） image speckle reduc- tion. This paper proposes a novel energy minimized regularization model for multichannel image denoising, which is an ...Abstract This paper aims at the multichannel synthetic aperture radar （SAR） image speckle reduc- tion. This paper proposes a novel energy minimized regularization model for multichannel image denoising, which is an extension of the non-local total variational model for gray-scale image. It contains two terms, namely the vectorial data fidelity term and the non-local vectorial total variation term. The latter is constructed by high-dimensional non-local gradient that contains the structure information of the multichannel image. The existence and the uniqueness of the solution of the model are proved. A fixed point iterative algorithm is designed to acquire the solution of this model. The convergence property of this algorithm is proved as well. This model is applied to the multipolarimetric and multi-temporal RAI）ARSAT-2 images despeckling. The result shows that this model performs better than the original vectorial total variational model on texture preserving.展开更多
The relation between the toal variation of classical field theory and the multisymplectic structure is shown. Then the multisymplectic structure and the corresponding multisymplectic conservation of the coupled nonlin...The relation between the toal variation of classical field theory and the multisymplectic structure is shown. Then the multisymplectic structure and the corresponding multisymplectic conservation of the coupled nonlinear Schroedinger system are obtained directly from the variational principle.展开更多
The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is...The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation （TV） and image morphology transform （specifically top-hat transform and bottom- hat transform） have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es- timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the ill-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition.展开更多
There is little low-and-high frequency information on seismic data in seismic exploration,resulting in narrower bandwidth and lower seismic resolution.It considerably restricts the prediction accuracy of thin reservoi...There is little low-and-high frequency information on seismic data in seismic exploration,resulting in narrower bandwidth and lower seismic resolution.It considerably restricts the prediction accuracy of thin reservoirs and thin interbeds.This study proposes a novel method to constrain improving seismic resolution in the time and frequency domain.The expected wavelet spectrum is used in the frequency domain to broaden the seismic spectrum range and increase the octave.In the time domain,the Frobenius vector regularization of the Hessian matrix is used to constrain the horizontal continuity of the seismic data.It eff ectively protects the signal-to-noise ratio of seismic data while the longitudinal seismic resolution is improved.This method is applied to actual post-stack seismic data and pre-stack gathers dividedly.Without abolishing the phase characteristics of the original seismic data,the time resolution is signifi cantly improved,and the structural features are clearer.Compared with the traditional spectral simulation and deconvolution methods,the frequency distribution is more reasonable,and seismic data has higher resolution.展开更多
A novel image restoration model coupling with a gradient fidelity term based on adaptive total variation is proposed in this paper. In order to choose proper parameters, the selection criteria were analyzed theoretica...A novel image restoration model coupling with a gradient fidelity term based on adaptive total variation is proposed in this paper. In order to choose proper parameters, the selection criteria were analyzed theoretically, and a simple scheme to demonstrate its validity was adopted experimentally. To make fair comparisons of performances of three models, the same numerical algorithm was used to solve partial differential equations. Both the international standard test image on Lena and HR image of CBERS-02B of Dalian city were used to verify the performance of the model. Experimental results illustrate that the new model not only preserved the edge and important details but also alleviated the staircase effect effectively.展开更多
This article introduces a fastmeshless algorithm for the numerical solution nonlinear partial differential equations(PDE)by Radial Basis Functions(RBFs)approximation connected with the Total Variation(TV)-basedminimiz...This article introduces a fastmeshless algorithm for the numerical solution nonlinear partial differential equations(PDE)by Radial Basis Functions(RBFs)approximation connected with the Total Variation(TV)-basedminimization functional and to show its application to image denoising containing multiplicative noise.These capabilities used within the proposed algorithm have not only the quality of image denoising,edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images.It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of dependence on a mesh or integration procedure.The numerical investigations and corresponding examples prove the effectiveness of the recommended algorithm regarding the robustness and visual improvement as well as peak-signal-to-noise ratio(PSNR),signal-to-noise ratio(SNR),and structural similarity index(SSIM)corresponded to the current conventional TV-based schemes.展开更多
A novel reference-driven method for MR image reconstruction based on wavelet sparsity and nonlocal total variation（NLTV）is proposed.Utilizing the sparsity of the difference image between the target image and the mot...A novel reference-driven method for MR image reconstruction based on wavelet sparsity and nonlocal total variation（NLTV）is proposed.Utilizing the sparsity of the difference image between the target image and the motion-compensated reference image in wavelet transform domain,the proposed method does not need to estimate contrast changes and therefore increases computational efficiency.Additionally,NLTV regularization is applied to preserve image details and features without blocky effects.An efficient alternating iterative algorithm is used to estimate motion effects and reconstruct the difference image.Experimental results demonstrate that the proposed method can significantly reduce sampling rate or improve the quality of the reconstructed image alternatively.展开更多
As an important part of water level warning in water conservancy projects,often due to the influence of environmental factors such as light and stains,the acquired water gauge images have sticky,broken and bright spot...As an important part of water level warning in water conservancy projects,often due to the influence of environmental factors such as light and stains,the acquired water gauge images have sticky,broken and bright spot conditions,which affect the identification of water gauges.To solve this problem,a water gauge image denoising model based on improved adaptive total variation is proposed.Firstly,the regular term exponent in the adaptive total variational equation is changed to an inverse cosine function;secondly,the differential curvature is used to distinguish the image noise points and increase the smoothing strength at the noise points;finally,according to the characteristics of the gradient mode and adaptive gradient threshold after Gaussian filtering,the New model can adaptively denoise in the smooth area and protect the edge area,so as to have the characteristics of both edge-preserving denoising.The experimental results show that the new model has a great improvement in image vision,higher iteration efficiency and an average increase of 1.6 dB in peak signal-to-noise ratio,and an average increase of 9%in structural similarity,which is more beneficial to practical applications.展开更多
Compton scattering imaging is a novel radiation imaging method using scattered photons.Its main characteristics are detectors that do not have to be on the opposite side of the source,so avoiding the rotation process....Compton scattering imaging is a novel radiation imaging method using scattered photons.Its main characteristics are detectors that do not have to be on the opposite side of the source,so avoiding the rotation process.The reconstruction problem of Compton scattering imaging is the inverse problem to solve electron densities from nonlinear equations,which is ill-posed.This means the solution exhibits instability and sensitivity to noise or erroneous measurements.Using the theory for reconstruction of sparse images,a reconstruction algorithm based on total variation minimization is proposed.The reconstruction problem is described as an optimization problem with nonlinear data-consistency constraint.The simulated results show that the proposed algorithm could reduce reconstruction error and improve image quality,especially when there are not enough measurements.展开更多
The relatively long scan time is still a bottleneck for both clinical applications and research of magnetic resonance imaging. To reduce the data acquisition time, we propose a novel fast magnetic resonance imaging me...The relatively long scan time is still a bottleneck for both clinical applications and research of magnetic resonance imaging. To reduce the data acquisition time, we propose a novel fast magnetic resonance imaging method based on parallel variable-density spiral acquisition, which combines undersampling optimization and nonlocal total variation reconstruction. The undersampling optimization promotes the incoherence of resultant aliasing artifact via the ＂worst-case＂ residual error metric, and thus accelerates the data acquisition. Moreover, nonlocal total variation reconstruction is utilized to remove such an incoherent aliasing artifact and so improve image quality. The feasibility of the proposed method is demonstrated by both numerical phantom simulation and in vivo experiment. The experimental results show that the proposed method can achieve high acceleration factor and effectively remove an aliasing artifact from data undersampling with well-preserved image details. The image quality is better than that achieved with the total variation method.展开更多
Controlled aliasing in parallel imaging results in higher acceleration （CAIPIRINHA） for simultaneous multislice imaging has been proposed recently, which combines multiband excitation and phase cycling techniques to...Controlled aliasing in parallel imaging results in higher acceleration （CAIPIRINHA） for simultaneous multislice imaging has been proposed recently, which combines multiband excitation and phase cycling techniques to reduce scan time and improve subsequent imaging reconstruction. In this work, the total variation （TV） regularization method is used to further improve CAIPIRINHA. The TV regularization uses an edge-preserving prior, which establishes a relationship between neighboring pixels for image reconstruction. It reduces artifacts and suppresses noise amplification simultaneously. The results are presented with a standard eight-channel head coil with an acceleration factor of 4, where the TV-regularized CAIPIRINHA generates an improved reconstruction as compared with a typical nonregularized CAIPIRINHA.展开更多
基金supported in part by the Natural Science Foundation of Xinjiang Uygur Autonomous Region under Grant 2022D01B184the National Natural Science Foundation of China under Grant 62301117,62131005.
文摘Covert communication guarantees the security of wireless communications via hiding the existence of the transmission.This paper focuses on the first and second order asymptotics of covert communication in the AWGN channels.The covertness is measured by the total variation distance between the channel output distributions induced with and without the transmission.We provide the exact expressions of the maximum amount of information that can be transmitted with the maximum error probability and the total variation less than any small numbers.The energy detection and the random coding are employed to prove our results.We further compare our results with those under relative entropy.The results show how many additional amounts of information can be transmitted covertly when changing the covertness constraint to total variation.
基金funded by National Nature Science Foundation of China,grant number 61302188。
文摘For addressing impulse noise in images, this paper proposes a denoising algorithm for non-convex impulse noise images based on the l_(0) norm fidelity term. Since the total variation of the l_(0) norm has a better denoising effect on the pulse noise, it is chosen as the model fidelity term, and the overlapping group sparse term combined with non-convex higher term is used as the regularization term of the model to protect the image edge texture and suppress the staircase effect. At the same time, the alternating direction method of multipliers, the majorization–minimization method and the mathematical program with equilibrium constraints were used to solve the model. Experimental results show that the proposed model can effectively suppress the staircase effect in smooth regions, protect the image edge details, and perform better in terms of the peak signal-to-noise ratio and the structural similarity index measure.
基金Supported by Open Fund of Key Laboratory of Anhui Higher Education Institutes (CS2021-07)the National Natural Science Foundation of China (61701004)Outstanding Young Talents Support Program of Anhui Province (gxyq2021178)。
文摘In this paper, we propose a novel shear gradient operator by combining the shear and gradient operators. The shear gradient operator performs well to capture diverse directional information in the image gradient domain. Based on the shear gradient operator, we extend the total variation(TV) norm to the shear total variation(STV) norm by adding two shear gradient terms. Subsequently, we introduce a shear total variation deblurring model. Experimental results are provided to validate the ability of the STV norm to capture the detailed information. Leveraging the Block Circulant with Circulant Blocks(BCCB) structure of the shear gradient matrices, the alternating direction method of multipliers(ADMM) algorithm can be used to solve the proposed model efficiently. Numerous experiments are presented to verify the performance of our algorithm for non-blind image deblurring.
基金The National Basic Research Program of China(973Program)(No.2011CB707904)the National Natural Science Foundation of China(No.61201344,61271312,61073138)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092110023,20120092120036)the Natural Science Foundation of Jiangsu Province(No.BK2012329)
文摘A new method for reconstructing the compressed sensing color image by solving an optimization problem based on total variation in the quaternion field is proposed, which can effectively improve the reconstructing ability of the color image. First, the color image is converted from RGB （red, green, blue） space to CMYK （cyan, magenta, yellow, black） space, which is assigned to a quaternion matrix. Meanwhile, the quaternion matrix is converted into the information of the phase and amplitude by the Euler form of the quatemion. Secondly, the phase and amplitude of the quatemion matrix are used as the smoothness constraints for the compressed sensing （CS） problem to make the reconstructing results more accurate. Finally, an iterative method based on gradient is used to solve the CS problem. Experimental results show that by considering the information of the phase and amplitude, the proposed method can achieve better performance than the existing method that treats the three components of the color image as independent parts.
基金supported by the National Natural Science Foundation of China(61702251,41971424,61701191,U1605254)the Natural Science Basic Research Plan in Shaanxi Province of China(2018JM6030)+4 种基金the Key Technical Project of Fujian Province(2017H6015)the Science and Technology Project of Xiamen(3502Z20183032)the Doctor Scientific Research Starting Foundation of Northwest University(338050050)Youth Academic Talent Support Program of Northwest University(360051900151)the Natural Sciences and Engineering Research Council of Canada,Canada。
文摘This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorization by total variation constraint and graph regularization.The main contributions of our work are the following.First,total variation is incorporated into NMF to control the diffusion speed.The purpose is to denoise in smooth regions and preserve features or details of the data in edge regions by using a diffusion coefficient based on gradient information.Second,we add graph regularization into NMF to reveal intrinsic geometry and structure information of features to enhance the discrimination power.Third,the multiplicative update rules and proof of convergence of the TV-GNMF algorithm are given.Experiments conducted on datasets show that the proposed TV-GNMF method outperforms other state-of-the-art algorithms.
基金supported by the National Natural Science Foundation of China(61571241)the Industry-University-research Prospective Joint Project of Jiangsu Province(BY2014014)+2 种基金the Major Projects of Jiangsu Province University Natural Science Research(15KJA510002)the Jiangsu Province Graduate Research and Innovation Project(CXZZ130476)the Science Research Fund of NUPT(NY215169)
文摘In foggy weather, images of outdoor scene are usually characterized with poor visibility as well as faint color saturation. The degraded hazy images may have substantial negative impact on most computer vision systems. Thus image haze removal is of the practical significance in engineering. This paper proposes a fast and effective single image haze removal algorithm on the basis of the physics imaging model. To extract the global atmospheric light accurately, we exploit multiple prior rules underlying hazy images, and put forward a novel measurement to judge the likelihood that a pixel is regarded as the global atmospheric light. In addition, the rough transmission map is estimated through a multiscale fusion process based on the Laplace pyramid transform, and refined by a total variation model. Experimental results demonstrate the proposed method outperforms most of the state-of-the-art algorithms in terms of the dehazing quality, and achieves a trade-off between the computational efficiency and haze removal capability.
基金supported in part by NSFC Grant No.60702030supported in part by NSFC Grant No.10871075the wavelets and information processing program under a grant from DSTA,Singapore
文摘In this paper,we propose a discrepancy rule-based method to automatically choose the regularization parameters for total variation image restoration problems. The regularization parameters are adjusted dynamically in each iteration.Numerical results are shown to illustrate the performance of the proposed method.
基金Supported by the National High Technology Research and Development Program of China(863 Program)(2008AA12Z201)
文摘In this paper,we propose a new image denoising method that combines total variation(TV)method and wavelet shrinkage.In our method,a noisy image is decomposed into subbands of LL,LH,HL,and HH in wavelet domain.LL subband contains the low frequency coefficients along with less noise,which can be easily eliminated using TV-based method.More edges and other detailed information like textures are contained in the other three subbands,and we propose a shrinkage method based on the local variance to extract them from high frequency noise.Experimental results show that this method retains the edges and textures very well while removing noise.
基金the National Natural Science Foundation of China(Nos.11401318 and 11671004)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.15KJB110018)the Scientific Research Foundation of NUPT(No.NY214023)
文摘Directionality of image plays a very important role in human visual system and it is important prior information of image. In this paper we propose a weighted directional total variation model to reconstruct image from its finite number of noisy compressive samples. A novel self-adaption, texture preservation method is designed to select the weight. Inspired by majorization-minimization scheme, we develop an efficient algorithm to seek the optimal solution of the proposed model by minimizing a sequence of quadratic surrogate penalties. The numerical examples are performed to compare its performance with four state-of-the-art algorithms. Experimental results clearly show that our method has better reconstruction accuracy on texture images than the existing scheme.
基金supported by the National Natural Science Foundation of China(Nos.61072142,61271437,61201337)the Science Research Project of National University of Defense Technology of China(Nos.JC12-02-05,JC13-02-03)
文摘Abstract This paper aims at the multichannel synthetic aperture radar （SAR） image speckle reduc- tion. This paper proposes a novel energy minimized regularization model for multichannel image denoising, which is an extension of the non-local total variational model for gray-scale image. It contains two terms, namely the vectorial data fidelity term and the non-local vectorial total variation term. The latter is constructed by high-dimensional non-local gradient that contains the structure information of the multichannel image. The existence and the uniqueness of the solution of the model are proved. A fixed point iterative algorithm is designed to acquire the solution of this model. The convergence property of this algorithm is proved as well. This model is applied to the multipolarimetric and multi-temporal RAI）ARSAT-2 images despeckling. The result shows that this model performs better than the original vectorial total variational model on texture preserving.
基金The project supported by National Natural Science Foundation of China under Grant Nos. 10401033 and 10471145 and the Key Project of Knowledge Innovation of CAS under Grant No. KZCX1-SW-18
文摘The relation between the toal variation of classical field theory and the multisymplectic structure is shown. Then the multisymplectic structure and the corresponding multisymplectic conservation of the coupled nonlinear Schroedinger system are obtained directly from the variational principle.
基金supported by the National Natural Science Foundation of China(61301095)the Chinese University Scientific Fund(HEUCF130807)the Chinese Defense Advanced Research Program of Science and Technology(10J3.1.6)
文摘The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation （TV） and image morphology transform （specifically top-hat transform and bottom- hat transform） have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es- timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the ill-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition.
基金supported by the PetroChina Prospective,Basic,and Strategic Technology Research Project(No.2021DJ0606).
文摘There is little low-and-high frequency information on seismic data in seismic exploration,resulting in narrower bandwidth and lower seismic resolution.It considerably restricts the prediction accuracy of thin reservoirs and thin interbeds.This study proposes a novel method to constrain improving seismic resolution in the time and frequency domain.The expected wavelet spectrum is used in the frequency domain to broaden the seismic spectrum range and increase the octave.In the time domain,the Frobenius vector regularization of the Hessian matrix is used to constrain the horizontal continuity of the seismic data.It eff ectively protects the signal-to-noise ratio of seismic data while the longitudinal seismic resolution is improved.This method is applied to actual post-stack seismic data and pre-stack gathers dividedly.Without abolishing the phase characteristics of the original seismic data,the time resolution is signifi cantly improved,and the structural features are clearer.Compared with the traditional spectral simulation and deconvolution methods,the frequency distribution is more reasonable,and seismic data has higher resolution.
基金Supported by the National Basic Research Program of China ("973"Program)(2009CB72400603) the National Natural Science Foundation of China(6102700260972100)
文摘A novel image restoration model coupling with a gradient fidelity term based on adaptive total variation is proposed in this paper. In order to choose proper parameters, the selection criteria were analyzed theoretically, and a simple scheme to demonstrate its validity was adopted experimentally. To make fair comparisons of performances of three models, the same numerical algorithm was used to solve partial differential equations. Both the international standard test image on Lena and HR image of CBERS-02B of Dalian city were used to verify the performance of the model. Experimental results illustrate that the new model not only preserved the edge and important details but also alleviated the staircase effect effectively.
文摘This article introduces a fastmeshless algorithm for the numerical solution nonlinear partial differential equations(PDE)by Radial Basis Functions(RBFs)approximation connected with the Total Variation(TV)-basedminimization functional and to show its application to image denoising containing multiplicative noise.These capabilities used within the proposed algorithm have not only the quality of image denoising,edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images.It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of dependence on a mesh or integration procedure.The numerical investigations and corresponding examples prove the effectiveness of the recommended algorithm regarding the robustness and visual improvement as well as peak-signal-to-noise ratio(PSNR),signal-to-noise ratio(SNR),and structural similarity index(SSIM)corresponded to the current conventional TV-based schemes.
基金Supported by the National Natural Science Foundation of China(61077022)
文摘A novel reference-driven method for MR image reconstruction based on wavelet sparsity and nonlocal total variation（NLTV）is proposed.Utilizing the sparsity of the difference image between the target image and the motion-compensated reference image in wavelet transform domain,the proposed method does not need to estimate contrast changes and therefore increases computational efficiency.Additionally,NLTV regularization is applied to preserve image details and features without blocky effects.An efficient alternating iterative algorithm is used to estimate motion effects and reconstruct the difference image.Experimental results demonstrate that the proposed method can significantly reduce sampling rate or improve the quality of the reconstructed image alternatively.
文摘As an important part of water level warning in water conservancy projects,often due to the influence of environmental factors such as light and stains,the acquired water gauge images have sticky,broken and bright spot conditions,which affect the identification of water gauges.To solve this problem,a water gauge image denoising model based on improved adaptive total variation is proposed.Firstly,the regular term exponent in the adaptive total variational equation is changed to an inverse cosine function;secondly,the differential curvature is used to distinguish the image noise points and increase the smoothing strength at the noise points;finally,according to the characteristics of the gradient mode and adaptive gradient threshold after Gaussian filtering,the New model can adaptively denoise in the smooth area and protect the edge area,so as to have the characteristics of both edge-preserving denoising.The experimental results show that the new model has a great improvement in image vision,higher iteration efficiency and an average increase of 1.6 dB in peak signal-to-noise ratio,and an average increase of 9%in structural similarity,which is more beneficial to practical applications.
基金Project supported by the National Basic Research Program of China (Grant No. 2011CB707701)the National High Technology Research and Development Program of China (Grant Nos. 2009AA012200 and 2012AA011603)
文摘Compton scattering imaging is a novel radiation imaging method using scattered photons.Its main characteristics are detectors that do not have to be on the opposite side of the source,so avoiding the rotation process.The reconstruction problem of Compton scattering imaging is the inverse problem to solve electron densities from nonlinear equations,which is ill-posed.This means the solution exhibits instability and sensitivity to noise or erroneous measurements.Using the theory for reconstruction of sparse images,a reconstruction algorithm based on total variation minimization is proposed.The reconstruction problem is described as an optimization problem with nonlinear data-consistency constraint.The simulated results show that the proposed algorithm could reduce reconstruction error and improve image quality,especially when there are not enough measurements.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.81101030 and 61271132)
文摘The relatively long scan time is still a bottleneck for both clinical applications and research of magnetic resonance imaging. To reduce the data acquisition time, we propose a novel fast magnetic resonance imaging method based on parallel variable-density spiral acquisition, which combines undersampling optimization and nonlocal total variation reconstruction. The undersampling optimization promotes the incoherence of resultant aliasing artifact via the ＂worst-case＂ residual error metric, and thus accelerates the data acquisition. Moreover, nonlocal total variation reconstruction is utilized to remove such an incoherent aliasing artifact and so improve image quality. The feasibility of the proposed method is demonstrated by both numerical phantom simulation and in vivo experiment. The experimental results show that the proposed method can achieve high acceleration factor and effectively remove an aliasing artifact from data undersampling with well-preserved image details. The image quality is better than that achieved with the total variation method.
基金Project supported by the National Natural Science Foundation of China(Grant No.61671026)the Natural Science Foundation of Beijing,China(Grant No.7162112)
文摘Controlled aliasing in parallel imaging results in higher acceleration （CAIPIRINHA） for simultaneous multislice imaging has been proposed recently, which combines multiband excitation and phase cycling techniques to reduce scan time and improve subsequent imaging reconstruction. In this work, the total variation （TV） regularization method is used to further improve CAIPIRINHA. The TV regularization uses an edge-preserving prior, which establishes a relationship between neighboring pixels for image reconstruction. It reduces artifacts and suppresses noise amplification simultaneously. The results are presented with a standard eight-channel head coil with an acceleration factor of 4, where the TV-regularized CAIPIRINHA generates an improved reconstruction as compared with a typical nonregularized CAIPIRINHA.
