检索结果-内蒙古大学图书馆

conference on Real-Time image and Video processing

作者： Maheshwary, Priti Shirvaikar, Mukul Grecos, Christos AISECT Univ Comp Sci & Engn Dept Bhopal 462039 India Univ Texas Tyler Elect Engn Dept Tyler TX 75799 USA Cent Washington Univ Comp Sci Dept Ellensburg WA 98926 USA

ISBN: (数字)9781510618527

ISBN: (纸本)9781510618527

Video is fast becoming the most common medium for media content in the present era. It is especially helpful in security situations for the detection of criminal or threat-related activity. Police routinely use videos as evidence in the analysis of criminal cases. It is important in such applications to get a high-quality still image from such videos. However, there are situations where the images are blurred and have artifacts as they are extracted from moving video repositories. A practical solution to this problem is to sharpen these images using advanced processing techniques to obtain higher display quality. Due to vast amount of data, it is extremely important that any such enhancement technique satisfy real-time processing constraints, in order for it to be usable by the end user. In this paper, a blind image sharpness metric is proposed using a combination of edge and textural features. Edges can be detected using different methods like Canny, Sobel, Prewitt and Roberts that are commonly accepted in the image processing literature. The Canny edge detection method typically provides better results due to extra processing steps and can be effectively used as a model feature extractor for the image. Wavelet processing based on the db2, sym4, and haar is also utilized to extract texture features. The normalized luminance coefficients of natural images are known to obey the generalized Gaussian probability distribution. Consequently, this characteristic is utilized to extract statistical features in the regions of interest (ROI) and regions of non-interest respectively. The extracted features are then merged together to obtain the sharpened image. The principle behind image formation is to merge the wavelet decompositions of the two original images using fusion methods applied to the approximation and details coefficients. The two images must be of the same size and are supposed to be associated with indexed images on a common color map. It is worth noting that t

关键词： image fusion image quality Cameras Edge detection image processing Distortion Video Feature extraction Wavelets Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

Estimated edge's points position. Optimized model for polarimetric SAR imagery

Estimated edge's points position. Optimized model for polari...

引用

Institute-of-Electrical-and-Electronics-Engineers (IEEE) Biennial Congress of Argentina

作者： Monferran, Daniel Sartarelli, Andres Univ Nacl Gen Sarmiento Inst Ind Dept Sistemas Informac Juan Maria Gutierrez 1150 RA-1613 Buenos Aires DF Argentina Univ Nacl Gen Sarmiento Inst Desarrollo Humano Juan Maria Gutierrez 1150 RA-1613 Buenos Aires DF Argentina Univ Tecnol Nacl FRD San Martin 1171 RA-2804 Buenos Aires DF Argentina

ISBN: (纸本)9781538650325

The Polarimetric Synthetic Aperture Radar is a special type of radar widely used in remote sensing since it allows capturing high resolution long-range terrestrial images. PolSAR images contain a large volume of information and are also contaminated with speckle noise which is neither Gaussian nor additive, for this reason the automatic interpretation of PolSAR images is a very difficult task. The characteristics of this noise make it necessary to use statistical methods for processing and digital analysis in this type of images. The complex Wishart distribution is the statistical distribution model most used to work with images generated from polarimetric multilook data. This distribution is indexed by two parameters: Sigma the covariance matrix and L the equivalent number of looks used to form the image. It is necessary to work with a very precise L value, this has led to research works aimed at reducing the bias in their estimation. The importance of processing times in estimating the edge points position has led to analyze and compare the processing times consumed using different estimation methods. In this work, different edge points identification techniques using the complex Wishart distribution, maximum likelihood, stochastic distances and active contours are analyzed, with the aim of reducing the computational cost in the estimation of the position of the edge points for the segmentation of PolSAR images. By applying the signal model in discrete time, optimized analytical expressions are obtained to estimate the edge points position with a lower computational cost. For the graphic visualization of the results, the region edges with B-spline curves are delineated. As a significant fact, in the particular case of complex Wishart distribution, the new analytical expression developed does not include the equivalent number of looks L. With Montecarlo experiments in simulated and real PolSAR images, the reduction of processing times is evaluated.

关键词： Covariance matrices image edge detection Synthetic aperture radar image segmentation Computational modeling Radar imaging

来源：评论

学校读者我要写书评

暂无评论

Kernel Sparse Representation Based Dimensionality Reduction with Applications to image Classification 18

Kernel Sparse Representation Based Dimensionality Reduction ...

引用

3rd International conference on Intelligent Information processing (ICIIP)

作者： Zhang, Di He, Jiazhong Zhao, Yun Guangdong Med Univ Dongguan Guangdong Peoples R China Shaoguan Univ Shaoguan Guangdong Peoples R China

ISBN: (纸本)9781450364966

Sparse representation is a statistical image modeling technique and has been successful used in image classification. In this paper, we present a dimensionality reduction method that well fits sparse representation in the kernel space. The proposed method maximizes the between-class reconstruction residual error while minimizes the within-class reconstruction residual error in the kernel space, thus improves the recognition accuracy of the sparse representation-based classifier. Experiments on PIE, the extended Yale B, and USPS databases demonstrates the effectiveness of the proposed method.

关键词： sparse representation kernel methods dimensionality reduction image classification

来源：评论

学校读者我要写书评

暂无评论

Blind Video Quality Assessment Based on Human Visual Characteristic

Blind Video Quality Assessment Based on Human Visual Charact...

引用

IEEE International Symposium on Parallel and Distributed processing with Applications and IEEE International conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Shiyu Zhou Xiqing Liu Yuanbing Tian Bin Fu Xiuyan Xia Jin Ge China Unicom Network Technology Research Institute Beijing China Zhiyou Open Source Communication Research Institute (Beijing) Co. Ltd Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781728152103

Based human visual speed perception characteristic, a video quanlity assessment(VQA) algorithm is introduced in the paper. Natural video statistics features extraction and weighting factors are incorporated in the scheme. In the VQA, considering the impact both video content itself and HVS's characteristic on human subjective perception, we propose weighting factors to scale the effect of those features, and it contains two parts: motion information and perception noise. And natural video statistics features relate to the spatial and temporal domain are extracted. The weighting factors would be used to combine both the temporal and spatial features, then generate the quality of each frame. Finally, the video quality score can be obtained by pooling scheme. LIVE database, EPFL-PoliMI database and some other generated test videos were used in our experiments, and the results indicate our model has outstanding performance.

关键词： feature extraction image denoising image motion analysis statistical analysis video signal processing visual databases image motion analysis visual databases Video signal processing image denoising Feature extraction Videotapes Quality assessment statistical methods statistical analysis WEIGHTING FACTORS

来源：评论

学校读者我要写书评

暂无评论

Fake Colorized image Detection with Channel-wise Convolution based Deep-learning Framework 10

Fake Colorized Image Detection with Channel-wise Convolution...

引用

10th Asia-Pacific-Signal-and-Information-processing-Association Annual Summit and conference (APSIPA ASC)

作者： Zhuo, Long Tan, Shunquan Zeng, Jishen Li, Bin Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China Shenzhen Univ Coll Informat Engn Shenzhen Peoples R China Natl Engn Lab Big Data Syst Comp Technol Shenzhen Key Lab Media Secur Guangdong Key Lab Intelligent Informat Proc Shenzhen 518060 Peoples R China

ISBN: (纸本)9789881476852

Colorization is one remarkable emerging image manipulating technique, which maybe potentially used for illegal purpose. In this paper, we introduce WISERNet (Wider Separate-then-reunion Network), a recently proposed deep-learning based data-driven color image steganalyzer in the field of fake colorized image detection. We believe that statistical inconsistencies introduced by different automatic colorization methods can be captured by advanced deep-learning based data-driven color-image steganalyzers such as WISERNet. Experimental evidences reported in this paper supports our claims: the detection performance of our proposed detector obviously outperforms FCID-HIST and FCID-FE, two state-of-the-art hand-crafted features specific to fake colorized image detection. Please note that in our approach we have never explicitly utilized information from the specific channels other than the ordinary red, green, and blue color channel, which is completely different from prior works in this field.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

An Accelerated Variational Framework for Face Expression Recognition

An Accelerated Variational Framework for Face Expression Rec...

引用

IEEE International Black Sea conference on Communications and Networking (BlackSeaCom)

作者： Fan, Wentao Bouguila, Nizar Huaqiao Univ Dept Comp Sci & Technol Xiamen Peoples R China Concordia Univ Concordia Inst Informat Syst Engn Montreal PQ Canada

ISBN: (纸本)9781538670910

In this paper we examine the problem of the modeling of positive vectors that are naturally generated by several signal and image processing applications. We consider a statistical framework based on a Dirichlet process mixture of inverted Dirichlet distributions like the one previously proposed in ill. The choice of inverted Dirichlet is motivated by its flexibility to model positive features. The proposed approach can be viewed as an infinite inverted Dirichlet mixture model. As compared to [l], the infinite framework is learned via an accelerated variational approach. The accelerated variational approach offers a good compromise between frequentist techniques and purely Bayesian inference and improves the simple variational approach used in ill. The merits of the proposed model are validated via a challenging application that involves face expression recognition.

关键词： Mixture models Acceleration Face recognition Face conferences Bayes methods image processing"

来源：评论

学校读者我要写书评

暂无评论

Segmentation of Medical images with a Combination of Convolutional Operators and Adaptive Hidden Markov Model

Segmentation of Medical Images with a Combination of Convolu...

引用

IEEE International conference on Computer and Communications

作者： Guoliang Li Jinhong Sun Yinglei Song Schoo of Eecronics nd Inforion Science Jingsu Universiy of Science nd TechnoogySchoo of Eecronics nd Inforion Science Jingsu Universiy of Science nd TechnoogySchoo of Eecronics nd Inforion Science Jingsu Universiy of Science nd Technoogy

ISBN: (数字)9781728147437

ISBN: (纸本)9781728147444

Medical image segmentation is a problem of fundamental importance in medical image processing. The accurate segmentation of a medical image can provide important information for the diagnosis and treatment of many diseases. Since a medical image often contains noises and the objects in it are inherently complex in general, methods that can accurately segment an arbitrary medical image are still unavailable. In this paper, a new approach that combines convolutional operators and an adaptive Hidden Markov Model is developed for the segmentation of medical images. Specifically, the features associated with each pixel in a medical image are obtained with a set of convolutional operators. The semantic and spatial correlations among pixels in the image are then progressively captured by an adaptive Hidden Markov Model. The labels of the pixels can be efficiently obtained with a dynamic programming algorithm in linear time. Our experimental results show that this approach can achieve segmentation results with improved accuracy on a set of brain medical images.

关键词： Hidden Markov models image segmentation Medical diagnostic imaging Dynamic programming Feature extraction stochastic processes

来源：评论

学校读者我要写书评

暂无评论

Rectangular Bounding Process 32

Rectangular Bounding Process

引用

32nd conference on Neural Information processing Systems (NIPS)

作者： Fan, Xuhui Li, Bin Sisson, Scott A. Univ New South Wales Sch Math & Stat Sydney NSW Australia Fudan Univ Sch Comp Sci Shanghai Peoples R China

stochastic partition models divide a multi-dimensional space into a number of rectangular regions, such that the data within each region exhibit certain types of homogeneity. Due to the nature of their partition strategy, existing partition models may create many unnecessary divisions in sparse regions when trying to describe data in dense regions. To avoid this problem we introduce a new parsimonious partition model - the Rectangular Bounding Process (RBP) - to efficiently partition multi-dimensional spaces, by employing a bounding strategy to enclose data points within rectangular bounding boxes. Unlike existing approaches, the RBP possesses several attractive theoretical properties that make it a powerful non-parametric partition prior on a hypercube. In particular, the RBP is self-consistent and as such can be directly extended from a finite hypercube to infinite (unbounded) space. We apply the RBP to regression trees and relational models as a flexible partition prior. The experimental results validate the merit of the RBP in rich yet parsimonious expressiveness compared to the state-of-the-art methods.

关键词： stochastic systems

来源：评论

学校读者我要写书评

暂无评论

A Novel Parameter Estimation Method for Generalized Gamma Distribution Towards SAR Data processing

A Novel Parameter Estimation Method for Generalized Gamma Di...

引用

Asian and Pacific conference on Synthetic Aperture Radar (APSAR)

作者： Peng Zhang Beibei Li Mohamed El Yazid Boudaren Junkun Yan Ming Li Yan Wu National laboratory of Radar Signal Processing Xidian University Xi'an China School of Electronic Engineering Ecole Militaire Polytechnique Bordj El Bahri Algiers Algeria Remote Sensing Image Processing and Fusion Group School of Electronic Engineering Xidian University Xi'an China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

statistical modeling of synthetic aperture radar (SAR) data is a crucial step in SAR image processing. In this context, the generalized Gamma (GGamma) distribution, which generalizes many common distributions, has been recognized as a valid model. Parameter estimation remains, however, a challenging step that conditions the quality of model fitting to data and thus, of the required processing. In this paper, we propose a novel parameter estimation method for GGamma distribution in the log-domain, named as the maximum likelihood and logarithmic cumulants (ML-LC) method. The ML-LC method constructs a novel scale-independent shape parameter estimation in the log-domain based on the Mellin transform and maximum likelihood estimation, and proposes a feasible solution technique for the shape parameter based on the multistart local search (MLS), gradient descent (GD) and bisection methods. To assess the performance of our estimation method, we perform the goodness-of-fit test on SAR data. In addition, we apply the ML-LC method in some SAR data processing tasks covering image segmentation and classification. The results obtained confirm the interest of the proposed ML-LC method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

stochastic Speckle Discrimination with Time-tagged Photon Lists: Digging below the Speckle Noise Floor

引用

PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC 2019年第1005期131卷

作者： Walter, Alex B. Bockstiegel, Clinton Brandt, Timothy D. Mazin, Benjamin A. Univ Calif Santa Barbara Dept Phys Santa Barbara CA 93106 USA

We present an algorithm that uses the distribution of photon arrival times to distinguish speckles from incoherent sources, like planets and disks, in high-contrast images. Using simulated data, we show that our approach can overcome the noise limit from fluctuating speckle intensity. The algorithm is likely to be most advantageous when a coronagraph limits the coherent diffraction pattern in the image plane but the intensity is still strongly modulated by fast-timescale uncorrected stellar light, for example from atmospheric turbulence. These conditions are common at small inner working angles of highly corrected adaptive optics images and will allow probing of exoplanet populations at smaller angular separations. The technique requires a fast science camera that can temporally resolve the speckle fluctuations, and the detection of many photons per speckle decorrelation time. Because the algorithm directly extracts the incoherent light, standard differential imaging postprocessing techniques can be performed afterwards to further boost the signal.

关键词： methods: data analysis methods: statistical planets and satellites: detection techniques: high angular resolution techniques: image processing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：