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Self-adaptive spatial image denoising model based on scale correlation and SURE-LET in the nonsubsampled contourlet transform domain

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Science China(Information Sciences) 2014年第9期57卷 72-86页

作者： LIANG MeiYu DU JunPing LIU HongGang Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications

A novel self-adaptive image denoising model based on scale correlation and Stein’s unbiased risk estimate-linear expansion of thresholds(SURE-LET)in the nonsubsampled contourlet transform domain is proposed in this *** we implement the multidimensional and translation invariant decomposition for spatial images by the nonsubsampled contourlet transform,and establish the image cross-scale description *** combining the scale correlation,we make improvements for the existing SURE-LET denoising idea and establish the self-adaptive denoising *** scale correlation calculation is needed for the coefficients at different scales and sub-bands to determine whether the coefficients are retained or processed with the adaptive SURE-LET threshold *** meanwhile a new local context self-adaptive threshold strategy is proposed in the process of scale correlation *** results both on spatial images and standard images demonstrate that the proposed algorithm performs significantly better in terms of both the visual subjective evaluation and the quantitative objective *** method can achieve better noise suppression,and effectively retain image edge details.

关键词： spatial images image denoising nonsubsampled contourlet transform SURE-LET scale correlation

IMAGE FUSION BASED ON nonsubsampled contourlet transform

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IMAGE FUSION BASED ON NONSUBSAMPLED CONTOURLET TRANSFORM

2009 International Conference on Environmental Science and Information Application Technology

作者： LIU GANG1 LIN XUEHUI2 QIAN HONG1 HUANG GUOHONG3 1 (Shanghai University of Electric Power Shanghai Key Laboratory of Power Station Automation Technology Shanghai University of Electric Power Shanghai China 200090) 2 (Shenyang Bright Engineering Co. Ltd. Shenyang Liaoning China 110002) 3 (Dept.of Information Guangdong University of Technology Guangzhou 510006 China)

Image fusion is the process of generating a single combined image,which contains a more accurate description of the scene than the multiple images from different *** approaches have been developed for the combination of complementary information coming from input images in order to create a new image where the informative content is more suitable for human visual or machine *** contourlet transform（NSCT）can realize a flexible multiscale,multidirection,and shift-invariant image *** a result,when NSCT is introduced to image fusion,more information and better characteristics from the original images for fusion could be *** this paper,NSCT is proposed when different registered source images are *** with two distinct modes of fusion method in low-frequency and in high-frequency separately,the fused image will be obtained by inverse *** with the fusion method based on wavelet and other fusion methods,the experiments show that this approach can achieve better results than them.

关键词： Image Fusion nonsubsampled contourlet transform Salience/Match Measure

Saliency Preserved Image Fusion Using nonsubsampled contourlet transform

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Saliency Preserved Image Fusion Using Nonsubsampled Contourl...

2013年中国智能自动化学术会议

作者： Liang Xu Junping Du Qingping Li JangMyung Lee Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications Department of Electronics Engineering Pusan National University

The visual attention model inspired by the early primate visual system is a very important tool in image *** on the visual attention model, the paper proposes a novel saliency preserved image fusion algorithm with a nonsubsampled contourlet transform(NSCT).The basic idea is that the visual saliency map is first built on the coefficients of the NSCT using the visual attention model,and then is combined with the coefficients of the NSCT to form the activity level which is employed to select the final fused *** algorithm can transform successfully the visual sensitive information from source images into the fused image which contains abundant detailed contents and preserves effectively the saliency structure while enhances the image *** demonstrate that the proposed algorithm yields the encouraging results.

关键词： Saliency map nonsubsampled contourlet transform Image fusion

An Image Denoising Method Based on nonsubsampled contourlet transform with SQP Optimization

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An Image Denoising Method Based on Nonsubsampled Contourlet ...

第36届中国控制会议

作者： Chen Yang Yaozhong Yu Qingdong Li Xiwang Dong Zhang Ren School of Automation Scicence and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University

ISBN: (纸本)9781538629185

In this paper,we propose an image demising method based on nonsubsampled contourlet transform（NSCT） with successive quadratic programming（SQP） *** method can obtain the optimal threshold for each subband without the priori information of the noise variance using SQP optimization and generalized cross validation（GCV） *** the threshold is determined,a nonlinear threshold function is applied to overcome the inadequate of soft threshold and hard threshold *** experimental results show that the proposed method has a better performance than other contourlet-based image demising methods and outperforms on both visual quality and peak signal-to-noise ratio（PSNR）.

关键词： Image denoising nonsubsampled contourlet transform successive quadratic programming nonlinear threshold function generalized cross validation

Image Fusion Using Compressed Sensing in nonsubsampled contourlet transform Domain

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Image Fusion Using Compressed Sensing in Nonsubsampled Conto...

2013年中国智能自动化学术会议

作者： Fu Liu School of Information Science and Engineering Hunan International Economics University

Image fusion algorithm using compressed sensing theory in nonsubsampled contourlet transform(NSCT) domain is proposed,NSCT can provide better sparsity than wavelet transform in image *** the transform of NSCT,low-frequency coefficients of the image are preserved,only high-frequency coefficients are *** coefficients are calculated according to different fusion rules in low frequency and high frequency domain. In the reconstruction,OMP algorithm is used to recover the high-frequency coefficients and the image is reconstructed by inverse nonsubsampled contourlet *** with wavelet compressed sensing algorithms,simulation results demonstrate that the quality of reconstructed image can be greatly improved.

关键词： nonsubsampled contourlet transform Image fusion Multi-resolution Compressed sending

Image Quality Assessment Based on nonsubsampled contourlet transform

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Image Quality Assessment Based on Nonsubsampled Contourlet T...

第二十九届中国控制会议

作者： LI Junfeng,DAI Wenzhan,PAN Haipeng,WANG Huijiao Department of Automatic control,Zhejiang Sci-Tech University,HangZhou 310018,P.R.China

Objective image quality assessment（QA）,which automatically evaluates the image quality consistently with human perception,is essentially important for numerous image and video processing *** this paper,based on the characteristics of nonsubsampled contourlet coefficients of images and the correlativity indexes,a novel image quality assessment is ***,the reference image and the distorted images are decomposed into several levels by means of nonsubsampled contourlet transform *** nonsubsampled contourlet coefficients of the reference image（the distorted images）are as the reference sequences（the comparative sequences）.Secondly,calculate the correlativity indexes between the reference sequences and the comparative sequences ***,image quality assessment vector of every distorted image can be constructed based on the correlativity indexes and image quality can be *** algorithm makes full use of perfect integral comparison mechanism of the correlativity indexes and the well matching of nonsubsampled contourlet transform with multi-channel model of human visual *** results show that the proposed method improves accuracy and robustness of image quality prediction.

关键词： Image Quality Assessment nonsubsampled contourlet transform Fuzzy Similarity Included Angle Cosine

SAR Image Despeckling Using Scale Mixtures of Gaussians in the nonsubsampled contourlet Domain

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Chinese Journal of Electronics 2015年第1期24卷 205-211页

作者： CHANG Xia JIAO Licheng LIU Fang SHA Yuheng Institute of Image Processing and Understanding School of Mathematics and Information Science Beifang University of Nationalities Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China International Research Center for Intelligent Perception and Computation Xidian University School of Computer Science and Technology Xidian University

The edge and contour details in SAR images are important for subsequent processing tasks. The multiscale geometric analysis method — nonsubsampled contourlet transform(NSCT) is able to capture the geometric information of SAR images effectively. Describing the aggregation behavior of the neighborhoods coefficients, the scale mixtures of Gaussians model has exhibited favorable performances. A novel SAR image despeckling method is presented by constructing the scale mixtures of Gaussians model of NSCT. This method models the SAR images using the multiscale and multidirection information in NSCT domain. The dependency relationship of NSCT neighborhoods coefficients are also taken into consideration in our model. The speckle noise coefficients are shrinkaged by statistical prior estimation based on SAR image model constructed. Experimental results demonstrate that our method is advantageous at directional information preservation and the speckle restraint.

关键词： Synthetic aperture radar(SAR) image despeckling Stationary wavelet transform nonsubsampled contourlet transform Scale mixtures of Gaussians model.

Artificial immune kernel clustering network for unsupervised image segmentation

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Progress in Natural Science:Materials International 2008年第4期18卷 455-461页

作者： Wenlong Huang , Licheng Jiao Institute of Intelligent Information Processing, Xidian University, Xi’an 710071, China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

An immune kernel clustering network (IKCN) is proposed based on the combination of the artificial immune network and the sup- port vector domain description (SVDD) for the unsupervised image segmentation. In the network, a new antibody neighborhood and an adaptive learning coeffcient, which is inspired by the long-term memory in cerebral cortices are presented. Starting from IKCN algo- rithm, we divide the image feature sets into subsets by the antibodies, and then map each subset into a high dimensional feature space by a mercer kernel, where each antibody neighborhood is represented as a support vector hypersphere. The clustering results of the local support vector hyperspheres are combined to yield a global clustering solution by the minimal spanning tree (MST), where a predfined number of clustering is not needed. We compare the proposed methods with two common clustering algorithms for the artificial synthetic data set and several image data sets, including the synthetic texture images and the SAR images, and encouraging experimental results are obtained.

关键词： Artificial immune network Kernel mapping nonsubsampled contourlet transform Unsupervised image segmentation

A Novel Algorithm for Microcirculation Image Enhancement

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Chinese Journal of Biomedical Engineering(English Edition) 2010年第3期19卷 114-120页

作者： LI Hong-jun ZHAO Zhi-min JI Lei ZHANG Lin Nanjing University of Aeronautics and Astronautics Nanjing 210016 China

Microcirculation images often have low quality in acquisition process, which affect the following steps of process. This paper introduces enhancement algorithm based on nonsubsampled contourlet transform (NSCT). It analyzes the characteristics of the microcirculation images generated, and separates microcirculation images to light weight and the reflection weight. It also analyzes the construction method on NSCT and proves that this method can be applied on microcirculation image enhancement algorithm. To correct light weight of microcirculation image and obtain enhancement image the enhancement microcirculation image was not only superior to the original image visually, but also improved objective data obviously. The algorithms provide a new method to microcirculation image pre-processing and guide the latter steps of the image processing.

关键词： image enhancement microcirculation image nonsubsampled contourlet transform

维普期刊数据库