Video denoising via spatially adaptive coefficient shrinkage and threshold adjustment in Surfacelet transform domain

Many video denoising methods originated from methods designed for processing static two-dimensional images. Videos would be processed frame by frame, a process with a relatively high computational complexity, without taking into account the correlation information between frames. In this paper, a video denoising method using coefficient shrinkage and threshold adjustment based on Surfacelet transform (CSTA-ST) is proposed, which processes multiple frames of a video as an ensemble. Spatial correlation is used to define a weighted spatial energy. Each Surfacelet transform (ST) coefficient has a corresponding estimated energy value, in which the ST coefficients are grouped by. The similarity of the ST coefficients in a group determines the threshold of each ST coefficient. In addition, according to the neighborhood information of ST coefficients, the threshold is adjusted by a threshold adjustment factor. The coefficient shrinkage parameter is determined based on the adjusted threshold, and the ST coefficients are shrunk. Finally, the denoised video is obtained by the inverse ST using the shrunk coefficients. In experiments, video sequences with noise are tested, and the denoised results of the proposed method are compared with that of current denoising methods. The experimental results show that the proposed method significantly improves the peak signal-to- noise ratio (PSNR) and the structural similarity (SSIM) for various levels of noise and motion, and the ideal denoised visual effect is obtained.     

Despeckling SAR images based on a new probabilistic model in nonsubsampled contourlet transform domain

A method for synthetic aperture radar (SAR) image despeckling based on a probabilistic generative model in nonsubsampled contourlet transform (NSCT) domain was proposed. The shrinkage estimator in NSCT domain consists of a new type of likelihood ratio and prior ratio, both of which are dependent on the estimated masks for the NSCT coefficients. While the previous probabilistic approaches are restricted to parametric models, the limitation is eliminated and the hybrid density model is applied in this paper. The suggested approach does not make heavy assumptions on the NSCT coefficient distribution, so that it can handle complex NSCT coefficient structures. The likelihood ratio is composed of the hybrid density, and the prior ratio is equipped with the selective neighborhood systems to enhance the detail information. The method can effectively adapt the shrinkage estimator to the redundancy property of the NSCT. The proposed approach was applied to real SAR images despeckling and compared through the SAR image vision effect, the equivalent number of looks, and the edge sustain index. Experimental results show that the proposed approach outperforms previous works involved in the paper with the better despeckling result and edge preservation.     

Context-based lossless interband compression-extending CALIC

This paper proposes an interband version of CALIC (context-based, adaptive, lossless image codec) which represents one of the best performing, practical and general purpose lossless image coding techniques known today. Interband coding techniques are needed for effective compression of multispectral images like color images and remotely sensed images. It is demonstrated that CALIC's techniques of context modeling of DPCM errors lend themselves easily to modeling of higher-order interband correlations that cannot be exploited by simple interband linear predictors alone. The proposed interband CALIC exploits both interband and intraband statistical redundancies, and obtains significant compression gains over its intrahand counterpart. On some types of multispectral images, interband CALIC can lead to a reduction in bit rate of more than 20% as compared to intraband CALIC. Interband CALIC only incurs a modest increase in computational cost as compared to intraband CALIC.     

Metastable Zirconium Phosphate under Nanoconfinement with Superior Adsorption Capability for Water Treatment

In confined space with length scale of several nanometers, the phase behavior of matter, e.g., nucleation and crystallization, is completely different from its analogue in bulk. However, in environmental applications, the relationship between the nanoconfined crystallization behavior of inorganic crystals and their properties for pollutant removal is rarely elucidated. Herein, an unusual formation of zirconium phosphate (ZrP) crystals as a mixture of both thermodynamically stable α‐ and metastable γ‐phases inside the nanoconfinement of 7.9 nm pores of mesoporous polystyrene (MPS) is reported. This consequently changes the interaction between ZrP and toxic metal cations from nonspecific electrostatic attraction of normal α‐ZrP to highly specific inner‐sphere coordination of nanoconfined γ‐ZrP, which exhibits remarkable reactivity as well as reusability for the removal of toxic metals. The results of this study contribute to a better understanding of the use of nanoconfinement for the regulation of material properties.     

A Retrievable Data Perturbation Method Used in Privacy-Preserving in Cloud Computing

With the increasing popularity of cloud computing,privacy has become one of the key problem in cloud security.When data is outsourced to the cloud,for data owners,they need to ensure the security of their privacy;for cloud service providers,they need some information of the data to provide high QoS services;and for authorized users,they need to access to the true value of data.The existing privacy-preserving methods can＇t meet all the needs of the three parties at the same time.To address this issue,we propose a retrievable data perturbation method and use it in the privacy-preserving in data outsourcing in cloud computing.Our scheme comes in four steps.Firstly,an improved random generator is proposed to generate an accurate ＂noise＂.Next,a perturbation algorithm is introduced to add noise to the original data.By doing this,the privacy information is hidden,but the mean and covariance of data which the service providers may need remain unchanged.Then,a retrieval algorithm is proposed to get the original data back from the perturbed data.Finally,we combine the retrievable perturbation with the access control process to ensure only the authorized users can retrieve the original data.The experiments show that our scheme perturbs date correctly,efficiently,and securely.     

泥页岩水敏性对盐岩层塑性变形的影响

由于处在盐岩层夹层中的泥页岩水敏性的影响,经24小时吸附水化和渗透水化后的泥页岩膨胀压力高达36.44MPa。抑制泥页岩水敏性是控制盐岩层塑性变形的有效途径。     

基于网络断层扫描的拓扑推断

网络断层扫描是一种全新的网络测量技术,该技术结合了网络测量和统计推断,可以解决网络测量的部分难题。网络拓扑推断是网络断层扫描的重要应用之一,基于网络断层扫描的拓扑推断通过端到端的测量,即可推断网络内部的拓扑结构,而不需要网络内部节点的合作。本文系统总结了网络断层扫描在网络拓扑推断中的测量方法和推断算法,对比了当前的测量...     

RCAD l.0系统在轮胎设计中的应用

介绍了橡胶计算机辅助设计１０系统（ＲＣＡＤ１０系统）及其在新产品１０－１５农机具轮胎设计中的应用，并与传统设计方法进行了比较。比较结果：用ＲＣＡＤ１０系统设计，机头宽度窄８ｍｍ，胎面胶用量少０４ｋｇ，且新产品设计周期从７ｄ缩短至１ｄ。     

Model-based adaptive resolution upconversion of degraded images

Resolution upconversion of a degraded image is an ill-posed inverse problem that is even harder than video superresolution due to lack of redundant observations from reference frames. To overcome this difficulty an adaptive 2D piecewise autoregressive (PAR) model is used to strengthen the constraints on the solution of the inverse problem. The PAR model can be fit to local image waveforms by adjusting its parameters. But estimating the model parameters needs the knowledge of the very original high-resolution pixels to be estimated by the model. We resolve this chicken-and-egg dilemma by adaptive nonlinear least-squares joint estimation of both model parameters and original pixels. This non-linear estimation problem is solved by the method of structured total least-squares, constrained by the degradation function (e.g., the point spread function of a camera plus noises) that forms the observed low-resolution image. As such, this work offers a unified general framework for joint upsampling, deconvolution, and denoising. Moreover, the upsampling can be carried out at an arbitrary scale rather than power of two. Experiments show that the proposed NEARU technique outperforms current methods in both PSNR and subjective visual quality, and its advantage becomes greater for larger scaling factors.     

Improvement of color video demosaicking in temporal domain.

Color demosaicking is critical to the image quality of digital still and video cameras that use a single-sensor array. Limited by the mosaic sampling pattern of the color filter array (CFA), color artifacts may occur in a demosaicked image in areas of high-frequency and/or sharp color transition structures. However, a color digital video camera captures a sequence of mosaic images and the temporal dimension of the color signals provides a rich source of information about the scene via camera and object motions. This paper proposes an inter-frame demosaicking approach to take advantage of all three forms of pixel correlations: spatial, spectral, and temporal. By motion estimation and statistical data fusion between adjacent mosaic frames, the new approach can remove much of the color artifacts that survive intra-frame demosaicking and also improve tone reproduction accuracy. Empirical results show that the proposed inter-frame demosaicking approach consistently outperforms its intra-frame counterparts both in peak signal-to-noise measure and subjective visual quality.