A new two-step variational model for multiplicative noise removal with applications to texture images

Multiplicative noise removal problems have attracted much attention in recent years.Unlike additive noise,multiplicative noise destroys almost all information of the original image,especially for texture images.Motivated by the TV-Stokes model,we propose a new two-step variational model to denoise the texture images corrupted by multiplicative noise with a good geometry explanation in this paper.In the first step,we convert the multiplicative denoising problem into an additive one by the logarithm transform and propagate the isophote directions in the tangential field smoothing.Once the isophote directions are constructed,an image is restored to fit the constructed directions in the second step.The existence and uniqueness of the solution to the variational problems are proved.In these two steps,we use the gradient descent method and construct finite difference schemes to solve the problems.Especially,the augmented Lagrangian method and the fast Fourier transform are adopted to accelerate the calculation.Experimental results show that the proposed model can remove the multiplicative noise efficiently and protect the texture well.

A Review of Image Steganography Based on Multiple Hashing Algorithm

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

Fast recognition using convolutional neural network for the coal particle density range based on images captured under multiple light sources

A method based on multiple images captured under different light sources at different incident angles was developed to recognize the coal density range in this study.The innovation is that two new images were constructed based on images captured under four single light sources.Reconstruction image 1 was constructed by fusing greyscale versions of the original images into one image,and Reconstruction image2 was constructed based on the differences between the images captured under the different light sources.Subsequently,the four original images and two reconstructed images were input into the convolutional neural network AlexNet to recognize the density range in three cases:-1.5(clean coal) and+1.5 g/cm^(3)(non-clean coal);-1.8(non-gangue) and+1.8 g/cm^(3)(gangue);-1.5(clean coal),1.5-1.8(middlings),and+1.8 g/cm^(3)(gangue).The results show the following:(1) The reconstructed images,especially Reconstruction image 2,can effectively improve the recognition accuracy for the coal density range compared with images captured under single light source.(2) The recognition accuracies for gangue and non-gangue,clean coal and non-clean coal,and clean coal,middlings,and gangue reached88.44%,86.72% and 77.08%,respectively.(3) The recognition accuracy increases as the density moves further away from the boundary density.

Three-dimensional positions of scattering centers reconstruction from multiple SAR images based on radargrammetry

A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.

Classification of hyperspectral remote sensing images based on simulated annealing genetic algorithm and multiple instance learning

A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.

Multiple Images Steganography of JPEG Images Based on Optimal Payload Distribution

Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission.Currently,the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible inmultiple cover images to improve the detection error rate of stego images.In order to enable the payloads to be accurately and efficiently distributed in each cover image,this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution.Firstly,the algorithm uses the principle of dynamic programming to redistribute the payloads of the cover images to reduce the time required in the process of payloads distribution.Then,by reducing the difference between the features of the cover images and the stego images to increase the detection error rate of the stego images.Secondly,this paper uses a data decomposition mechanism based on Vandermonde matrix.Even if part of the data is lost during the transmission of the secret messages,as long as the data loss rate is less than the data redundancy rate,the original secret messages can be recovered.Experimental results show that the method proposed in this paper improves the efficiency of payloads distribution compared with existing multiple images steganography.At the same time,the algorithm can achieve the optimal payload distribution of multiple images steganography to improve the anti-statistical detection performance of stego images.

Retrieving chlorophyll content and equivalent water thickness of Moso bamboo(Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework

Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content inversion.However,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered.Therefore,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation levels.Quantitative inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were derived.The scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were calculated.The results showed that LAI,CCC,and CEWT were inversely related with PPC-induced stress.When applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),respectively.Compared to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for CCC.The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.

A Method for Registering Multiple Range Images

This paper presents an algorithm for registering multiple range images, which is efficient and robust in the presence of noise and occlusion. The registration algorithm is an integration of the iterative closest point(ICP) algorithm with random sampling and least squares(LS) estimator. It iterates the processes of random sampling with conditional reject, estimation of motion parameters by using ICP algorithm and evaluation of the estimation. The algorithm first creates an octree spline of object surface to quickly compute point to surface distance and its closest point using trilinear interpolation. The advantages of the proposed method are the reduction of computational cost and robustness to outliers.

Multiple Targets Recognition for Highly-Compressed Color Images in a Joint Transform Correlator

In this paper, we are proposing a compression-based multiple color target detection for practical near real-time optical pattern recognition applications. By reducing the size of the color images to its utmost compression, the speed and the storage of the system are greatly increased. We have used the powerful Fringe-adjusted joint transform correlation technique to successfully detect compression-based multiple targets in colored images. The colored image is decomposed into three fundamental color components images (Red, Green, Blue) and they are separately processed by three-channel correlators. The outputs of the three channels are then combined into a single correlation output. To eliminate the false alarms and zero-order terms due to multiple desired and undesired targets in a scene, we have used the reference shifted phase-encoded and the reference phase-encoded techniques. The performance of the proposed compression-based technique is assessed through many computer simulation tests for images polluted by strong additive Gaussian and Salt & Pepper noises as well as reference occluded images. The robustness of the scheme is demonstrated for severely compressed images (up to 94% ratio), strong noise densities (up to 0.5), and large reference occlusion images (up to 75%).

Imaging of multiple myeloma: Current concepts

Medical imaging is of crucial importance for diagnosis and initial staging as well as for differentiation of multiple myeloma(MM)from other monoclonal plasma cell diseases.Conventional radiography represents the reference standard for diagnosis of MM due to its wide availability and low costs despite its known limitations such as low sensitivity,limited specificity and its inability to detect extraosseous lesions.Besides conventional radiography,newer cross-sectional imaging modalities such as whole-body low-dose computed tomography(CT),whole-body magnetic resonance imaging(MRI)and18F-fluorodeoxyglucose(FDG)positron emission tomography(PET)/CT are available for the diagnosis of osseous and extraosseous manifestations of MM.Whole-body low-dose CT is used increasingly,replacing conventional radiography at selected centers,due to its higher sensitivity for the detection of osseous lesions and its ability to diagnose extraosseous lesions.The highest sensitivity for both detection of bone marrow disease and extraosseous lesions can be achieved with whole-body MRI and18F-FDG PET/CT.According to current evidence,MRI is the most sensitive method for initial staging while18F-FDG PET/CT allows monitoring of treatment of MM.There is an evolving role for assessment of treatment response using newer MR imagingtechniques.Future studies are needed to further define the exact role of the different imaging modalities for individual risk stratification and therapy monitoring.

The role of Epstein-Barr virus in multiple sclerosis:from molecular pathophysiology to in vivo imaging

Multiple sclerosis(MS) is a disease of the central nervous system characterized by inflammation, demyelination, and neuronal damage. Environmental and genetic factors are associated with the risk of developing MS, but the exact cause still remains unidentified. Epstein-Barr virus(EBV), vitamin D, and smoking are among the most well-established environmental risk factors in MS. Infectious mononucleosis, which is caused by delayed primary EBV infection, increases the risk of developing MS. EBV may also contribute to MS pathogenesis indirectly by activating silent human endogenous retrovirus-W. The emerging B-cell depleting therapies, particularly anti-CD20 agents such as rituximab, ocrelizumab, as well as the fully human ofatumumab, have shown promising clinical and magnetic resonance imaging benefit. One potential effect of these therapies is the depletion of memory B-cells, the primary reservoir site where EBV latency occurs. In addition, EBV potentially interacts with both genetic and other environmental factors to increase susceptibility and disease severity of MS. This review examines the role of EBV in MS pathophysiology and summarizes the recent clinical and radiological findings, with a focus on B-cells and in vivo imaging. Addressing the potential link between EBV and MS allows the better understanding of MS pathogenesis and helps to identify additional disease biomarkers that may be responsive to B-cell depleting intervention.

Magnetic resonance imaging correlates of bee sting induced multiple organ dysfunction syndrome: A case report

Occasionally systemic complications with high risk of death,such as multiple organ dysfunction syndrome(MODS),can occur following multiple bee stings.This case study reports a patient who presented with MODS,i.e.,acute kidney injury,hepatic and cardiac dysfunc-tion,after multiple bee stings.The standard clinical findings were then correlated with magnetic resonance imaging(MRI)findings,which demonstrates that MRI may be utilized as a simpler tool to use than other mul-tiple diagnostics.

Diffusion tensor imaging with multiple diffusion-weighted gradient directions

Diffusion tensor MRI （DT-MRI or DTI） is emerging as an important non-invasive technology for elucidating intemal brain structures. It has recently been utilized to diagnose a series of diseases that affect the integrity of neural systems to provide a basis for neuroregenerative studies. Results from the present study suggested that neural tissue is reconstructed with multiple diffusion-weighted gradient directions DTI, which varies from traditional imaging methods that utilize 6 gradient directions. Simultaneously, the diffusion tensor matrix is obtained by multiple linear regressions from an equation of echo signal intensity. The condition number value and standard deviation of fractional anisotropy for each scheme can be used to evaluate image quality. Results demonstrated that increasing gradient direction to some extent resulted in improved effects. Therefore, the traditional 6 and 15 directions should not be considered optimal scan protocols for clinical DTI application. In a scheme with 20 directions, the condition number and standard deviation of fractional anisotropy of the encoding gradients matrix were significantly reduced, and resulted in more clearly and accurately displayed neural tissue. Results demonstrated that the scheme with 20 diffusion gradient directions provided better accuracy of structural renderings and could be an optimal scan protocol for clinical DTI application.

Passive multiple reverse time migration imaging based on wave decomposition and normalized imaging conditions

With the development of seismic exploration,passive-source seismic data has attracted increasing attention.Ambient noise passive seismic sources exists widely in nature and industrial production.Passive seismic data is important in logging while drilling(LWD),large-scale structural exploration,etc.In this paper,we proposed a passive multiple reverse time migration imaging(PMRTMI)method based on wavefield decomposition and normalized imaging conditions method.This method differs from seismic interferometry in that it can use raw passive seismic data directly in RTM imaging without reconstruction of virtual active gather,and we use the wavefield decomposition method to eliminate the low frequency noise in RTM.Further,the energy normalized imaging condition is used in full wavefield decomposition,which can not only enhance the image quality of both edge and deep information but also overcome the wrong energy problem caused by uneven distribution of passive sources;furthermore,this method exhibits high efficiency.Finally,numerical examples with the Marmousi model show the effectiveness of the method.

First-order multiples imaging aided by water bottom

Surface-related multiples frequently propagate into the subsurface and contain abundant information on small reflection angles.Compared with the conventional migration of primaries,migration of multiples offers complementary illumination and a higher vertical resolution.However,crosstalk artifacts caused by unrelated multiples during reverse time migration(RTM)using multiples severely degrade the reliability and interpretation of the final migration images.Therefore,we proposed RTM using first-order receiver-side water-bottom-related multiples for eliminating crosstalk artifacts and enhancing vertical resolution.We first backward propagate the first-order receiver-side water-bottom-related multiples using a water-layer model,followed by saving the upper boundary wavefield.Then we produce the source wavefield using a seismic wavelet and the receiver wavefield by back-extrapolating the saved boundary.Finally,the cross-correlation imaging condition is applied to generate the final image.This method transforms the receiver-side multiples into primaries,followed by the conventional migration processing procedures.Numerical examples using synthetic datasets demonstrate that our method significantly enhances the imaging quality by eliminating crosstalk artifacts and improving the resolution.

Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging

Multiple sclerosis is a neurodegenerative and inflammatory disease, a hallmark of which is demyelinating lesions in the white matter. We hypothesized that alterations in white matter microstructures can be non-invasively characterized by advanced diffusion magnetic resonance imaging. Seven diffusion metrics were extracted from hybrid diffusion imaging acquisitions via classic diffusion tensor imaging, neurite orientation dispersion and density imaging, and q-space imaging. We investigated the sensitivity of the diffusion metrics in 36 sets of regions of interest in the brain white matter of six female patients(age 52.8 ± 4.3 years) with multiple sclerosis. Each region of interest set included a conventional T2-defined lesion, a matched perilesion area, and normal-appearing white matter. Six patients with multiple sclerosis(n = 5) or clinically isolated syndrome(n = 1) at a mild to moderate disability level were recruited. The patients exhibited microstructural alterations from normal-appearing white matter transitioning to perilesion areas and lesions, consistent with decreased tissue restriction, decreased axonal density, and increased classic diffusion tensor imaging diffusivity. The findings suggest that diffusion compartment modeling and q-spa ce analysis appeared to be sensitive for detecting subtle microstructural alterations between perilesion areas and normal-appearing white matter.

Correlations between hippocampal functional connectivity,structural changes,and clinical data in patients with relapsing-remitting multiple sclerosis:a case-control study using multimodal magnetic resonance imaging

Multiple sclerosis is associated with structural and functional brain alterations leading to cognitive impairments across multiple domains including attention,memory,and the speed of information processing.The hippocampus,which is a brain important structure involved in memory,undergoes microstructural changes in the early stage of multiple sclerosis.In this study,we analyzed hippocampal function and structure in patients with relapsing-remitting multiple sclerosis and explored correlations between the functional connectivity of the hippocampus to the whole brain,changes in local brain function and microstructure,and cognitive function at rest.We retrospectively analyzed data from 20 relapsing-remitting multiple sclerosis patients admitted to the Department of Neurology at the China-Japan Union Hospital of Jilin University,China,from April 2015 to November 2019.Sixteen healthy volunteers were recruited as the healthy control group.All participants were evaluated using a scale of extended disability status and the Montreal cognitive assessment within 1 week before and after head diffusion tensor imaging and functional magnetic resonance imaging.Compared with the healthy control group,the patients with relapsing-remitting multiple sclerosis had lower Montreal cognitive assessment scores and regions of simultaneously enhanced and attenuated whole-brain functional connectivity and local functional connectivity in the bilateral hippocampus.Hippocampal diffusion tensor imaging data showed that,compared with the healthy control group,patients with relapsing-remitting multiple sclerosis had lower hippocampal fractional anisotropy values and higher mean diffusivity values,suggesting abnormal hippocampal structure.The left hippocampus whole-brain functional connectivity was negatively correlated with the Montreal cognitive assessment score(r=-0.698,P=0.025),and whole-brain functional connectivity of the right hippocampus was negatively correlated with extended disability status scale score(r=-0.649,P=0.042).The mean diffusivity value of the left hippocampus was negatively correlated with the Montreal cognitive assessment score(r=-0.729,P=0.017)and positively correlated with the extended disability status scale score(r=0.653,P=0.041).The right hippocampal mean diffusivity value was positively correlated with the extended disability status scale score(r=0.684,P=0.029).These data suggest that the functional connectivity and presence of structural abnormalities in the hippocampus in patients with relapse-remission multiple sclerosis are correlated with the degree of cognitive function and extent of disability.This study was approved by the Ethics Committee of China-Japan Union Hospital of Jilin University,China(approval No.201702202)on February 22,2017.

^(18)F-FDG PET/CT imaging for a gastrointestinal mantle cell lymphoma with multiple lymphomatous polyposis

Multiple lymphomatous polyposis(MLP)is an uncommon type of gastrointestinal lymphoma characterized by the presence of multiple polyps along the gastrointestinal tract.Most of this entity is in fact considered the counterpart of gastrointestinal tract involvement for mantle cell lymphoma(MCL).To our knowledge,there have been no reports on[fluorine-18]-fluorodeoxy-glucose(18F-FDG)-positron emission tomography(PET)/computed tomography(CT)imaging for gastrointestinal MCL with MLP.We present the results of 18F-FDG PET/CT imaging in a patient with gastrointestinal tract involvement of MCL showing continuous MLP from the stomach to the rectum and intestinal intussusception.FDG-PET/CT findings were false negative in typical MLP spreading widely over the gastrointestinal tract,but uptake was noted in large lesions with deep infiltration considered atypical as MLP.On FDG-PET/CT imaging,the Ki-67proliferative index,which is a cell proliferation marker,showed neither correlation with the presence of uptake nor the maximum standardized uptake value.

Intracolonic multiple pebbles in young adults:Radiographic imaging and conventional approach to a case

Most of the foreign bodies detected in adult gastroin- testinal systems are accidentally swallowed pins. In this study, we presented a case with intracolonic multiple pebbles. A 20-year-old man was admitted to emergency surgery policlinic for abdominal pain for 2 d without any alleviation or aggravation. His upright plain abdominal radiographic imaging revealed about 30-40 overt dense opacities in lumen of colonic segments, with oval and well shaped contours, each approximately 1 cm × 1 cm in size. The multiplanar reconstructions and three- dimensional images combined with sectional screening showed that all pebbles had passed completely into the colon and no foreign bodies had remained in the ileal segments. On psychiatric assessment, he was found to have immature personality features, difficulty in over- coming stressors and adaptation disorder. He recovered by conservative management and radiographic monitoring applied during his follow-up. Thus, it can be concluded that, in differential diagnosis of abdominal pain in adult ages, though less frequently seen than in children, gastrointestinal system foreign bodies should always be kept in mind and it should be considered that ingestion of pebbles may be one of the factors contributing to abdominal pain particularly in young adults with psychiatric problems. In such cases suspected of having foreign bodies which cannot be detected by plain films, abdominal tomography can be an alternative for diagnostic imaging.

Iterative Soft Decoding of Multiple Description Image over Wireless Channel

Motivated by recent results in multiple description image coding over wireless networks, we propose a scheme for transmission of multiple descriptions through hybrid packet loss and additive white Gaussian noise channel. Each description is coded into multiple bitstreams by applying SPIHT coding on wavelet trees along spatial orientations and each stream is further compressed using arithmetic code. Use of error resilient entropy coding (EREC) is proposed in literature for synchronization requirement of variable length codes, but EREC is not compatible with iterative soft-in soft-out decoding of arithmetic code at the receiver. We propose the application of EREC assisted by state and tail bits (ERECST) in conjunction with iterative decoding of arithmetic code at receiver for reconstructing the multiple description coded image over packet loss and Gaussian noise channel. Experimental results demonstrate that an additional gain of 7 dB in PSNR is obtained over existing scheme.