2010 International Conference on Wavelet Analysis and Pattern Recognition最新文献_第5页

Urban remote image fusion based on multi-characteristics 基于多特征的城市遥感图像融合

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576429

Xu-Hong Yang, Gang Liu, F. Huang

引用次数: 0

Two-dimensional periodic discrete wavelets bases 二维周期离散小波基

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576398

Zhi Shi, B. Peng

引用次数: 0

Infrared face recognition based on radiative energy and sub-block DCT in wavelet domain 基于辐射能量和小波域子块DCT的红外人脸识别

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576437

Xiao-Wei Liu, Zhihua Xie, Cui-Qun He, Guodon Liu

引用次数: 0

Unsupervised classification of forest from polarimetric interferometric SAR data using fuzzy clustering 基于模糊聚类的极化干涉SAR数据森林无监督分类

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576325

Huanmin Luo, E. Chen, Xiaowen Li, Jian Cheng, Min Li

{"title":"Unsupervised classification of forest from polarimetric interferometric SAR data using fuzzy clustering","authors":"Huanmin Luo, E. Chen, Xiaowen Li, Jian Cheng, Min Li","doi":"10.1109/ICWAPR.2010.5576325","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576325","url":null,"abstract":"Fuzzy clustering algorithms have been successfully applied to POLSAR classification, but not to POLInSAR. In this paper, a Fuzzy C Means (FCM) clustering algorithm integrating the complementary physical information and statistical property contained in both polarimetric and interferometric data, is used for POLInSAR classification. At first, the area dominated by volume scattering is extracted from polarimetric information using unsupervised H-A-Alpha k-means Wishart classifier with the physical scattering mechanisms of different terrain types; and the volume scattering area (forest area) is further segmented in the feature space of the relative optimal interferomet-ric coherence spectrum A1 and A2. Then a robust unsupervised fuzzy C means (FCM) classifier initialized with the results of the segmentation is applied to the polarimetric interferometric coherency data sets corresponding to the volume scattering area. This will not only take into account the scattering mechanisms of the data, so that the results of the classification have definite physical meaning, but also avoid the problem that the initial value of FCM algorithm is difficult to identify. The proposed method is evaluated and compared with k-means Wishart classifier using repeat pass E-SAR L band polarimetric interfer-ometric SAR data and the corresponding auxiliary image. Preliminary results show that the proposed method has better performance.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115495784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An adaptive fusion method based on regional feature for ALOS image 基于区域特征的ALOS图像自适应融合方法

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576454

Xiaoyan Wang, Yong Liu, Zhiyong Jiang

{"title":"An adaptive fusion method based on regional feature for ALOS image","authors":"Xiaoyan Wang, Yong Liu, Zhiyong Jiang","doi":"10.1109/ICWAPR.2010.5576454","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576454","url":null,"abstract":"Most Earth observation satellites provide both panchromatic images with a higher spatial resolution and multispectral images with a lower spatial resolution. Image fusion techniques can integrate the spatial detail of the panchromatic image and the spectral characteristics of the multispectral image into one image Exiting image fusion techniques such as the Intensity-Hue-Saturation (IHS) transform method, Brovey transform method and High Pass Filter (HPF) method may not be optimization while fusing the new generation commercial satellite image such as ALOS. The most serious problem is that the fused image usually has a notable deviation in visual appearance and spectral values from the original image. In this paper, we proposed a new fusion method for ALOS images, when adding the detail information of panchromatic image to the intensity component of multispectral image, the weight coefficients are determined adaptively based on the structural similarity(SSIM) between the panchromatic image and the intensity component of the multispectral image. Experimental results indicate that this method is effective when fusing ALOS image.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"307 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132519909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Constructing section profile curve of turbine blade 构造涡轮叶片截面轮廓曲线

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576329

Yuanpeng Liu, Song Zhao, Xiaoyan Dong

引用次数: 1

Orthogonal sparsity preserving projections for feature extraction 特征提取中的正交稀疏性保持投影

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576322

Chao Lan, Xiaoyuan Jing, Qian Liu, Shi-Qiang Gao, Yong-Fang Yao

{"title":"Orthogonal sparsity preserving projections for feature extraction","authors":"Chao Lan, Xiaoyuan Jing, Qian Liu, Shi-Qiang Gao, Yong-Fang Yao","doi":"10.1109/ICWAPR.2010.5576322","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576322","url":null,"abstract":"Sparse representation has been extensively studied in the signal processing community, which surprisingly pointed out that one target signal can be accurately represented as a linear combination of very few measurement signals, often called atoms, in a given dictionary. This discovery has soon been employed to the field of pattern recognition and more recently, given rise to a newly developed unsupervised feature extraction method named sparsity preserving projections (SPP), which aims at seeking a linear embedded space where the sparse reconstructive relations among the data in the dictionary can be preserved. However, SPP is non-orthogonal and still has some space for improvement. Specially, by taking into consideration the preservation of some neat property of a dictionary, this paper presents an orthogonal sparsity preserving projections (OSPP). OSPP iteratively calculate a projective vector which can preserve the sparse reconstructive relations as SPP dose, and at the same enforcing it to be orthogonal to all previously obtained vectors. Empirical study shows that OSPP has more powerful sparsity preserving ability than SPP and hence is expected to have better classification performance, since sparsity is potentially related to discrimination. Experiments on the public Yale face databases validate the effectiveness of OSPP, as compared with several representative unsupervised feature extraction methods.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128811369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Wavelet analysis in transient based protection for power system high voltage transmission line 电力系统高压输电线路暂态保护中的小波分析

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576409

M. Xia, Yibin Huang

引用次数: 3

Design and implement of high resolution still image compression and storage system 高分辨率静态图像压缩存储系统的设计与实现

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576442

Zhe Chen, Zongtao Duan, Zhao-yun Sun, Ji'an Tao, L. Yao

引用次数: 4

Extraction of vibration feature using purpose designed wavelets for heart diagnosis 利用设计的小波提取心脏振动特征

2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576406

B. Tovar, W. J. Wang, J. Torry

引用次数: 0