检索结果-内蒙古大学图书馆

5th International Symposium on Multispectral image processing and pattern recognition

作者： Luo, Wenfei Zhong, Liang Zhang, Bing Luo, Shoumei Chinese Acad Sci Inst Remote Sensing Applicat Beijing 100101 Peoples R China South China Normal Univ Sch Geog Sci Guangzhou 510631 Guangdong Peoples R China

ISBN: (纸本)9780819469519

pattern recognition has been successfully applied to target detection. The characteristic of target pattern determines the detection ability in pattern recognition. The pattern of spectral signature at hyperspectral resolution provides more distinguished spectral feature for target detection and then improves the detection ability. However, hyperspectral image has limitation on low resolution in spatial. Therefore, this article focus on analyze on the target detection ability at the sub-pixel scale in different spatial resolution, considering two critical factors, i.e. spatial response in sensor and background interferer. Experiment data is simulated by inducing these two factors. Target-to-Clutter-Ratio (TCR2) curve and Receiver Operating Characteristic (ROC) curve with Uniform Target Detector (UTD) analyze on the simulated data. We conclude that spatial response of the sensor and the background interferer induce uncertainty into target detection ability and usually weakens it. It gives rise to a new requirement for hyperspectral target detection that should be considerate for the effect caused by spatial resolution.

关键词： hyperspectral target detection spatial resolution

来源：评论

学校读者我要写书评

暂无评论

A time-efficient method for anomaly detection in hyperspectral images

引用

IEEE TRANSACTIONS ON GEOSCIENCE AND remote sensing 2007年第12期45卷 3894-3904页

作者： Duran, Olga Petrou, Maria Imperial Coll London Dept Elect & Elect Engn Commun & Signal Proc Grp London SW7 2AZ England

We propose a computationally efficient method for determining anomalies in hyperspectral data. In the first stage of the algorithm, the background classes, which are the dominant classes in the image, are found. The method consists of robust clustering of a randomly chosen small percentage of the image pixels. The clusters are the representatives of the background classes. By using a subset of the pixels instead of the whole image, the computation is sped up, and the probability of including outliers in the background model is reduced. Anomalous pixels are the pixels with spectra that have large relative distances from the cluster centers. Several clustering techniques are investigated, and experimental results using realistic hyperspectral data are presented. A self-organizing map clustered using the local minima of the U-matrix (unified distance matrix) is identified as the most reliable method for background class extraction. The proposed algorithm for anomaly detection is evaluated using realistic hyperspectral data, is compared with a state-of-the-art anomaly detection algorithm, and is shown to perform significantly better.

关键词： Hyperspectral imaging Hyperspectral sensors Layout Clustering algorithms Signal processing algorithms Pixel Military aircraft Gaussian distribution Robustness Data mining

来源：评论

学校读者我要写书评

暂无评论

A spectral preservation fusion method based on band ratio and weighted combination

A spectral preservation fusion method based on band ratio an...

引用

5th International Symposium on Multispectral image processing and pattern recognition

作者： Zhu, Wenquan Pang, Xinhua Pan, Yaozhong Jia, Bin Yang, Xiaoqiong Beijing Normal Univ Coll Resources Sci & Technol State Key Lab Earth Surface Proc & Resource Ecol Beijing 100875 Peoples R China

ISBN: (纸本)9780819469519

With the availability of multi-sensor data in the field of remote sensing, sensor fusion has emerged as a promising research area. This study presents a simple spectral preservation fusion approach based on band ratio and weighted combination. It injects spatial features into multi-spectral images to improve the spatial information, and adjusts the ratio between the high spatial resolution image and the multi-spectral image with a weight factor to reduce the color distortion. This method is applied to merge SPOT and LANDSAT (TM) images. Visual and statistical analysis prove that the technique presented here is clearly better than the conventional image fusion techniques for preserving the spectral properties with the spatial detail improved synchronously.

关键词： image fusion wavelet remote sensing color distortion IHS PCA

来源：评论

学校读者我要写书评

暂无评论

Research on classification of high-resolution remote sensing image

Research on classification of high-resolution remote sensing...

引用

MIPPR 2007: Automatic Target recognition and image Analysis;and Multispectral image Acquisition

作者： Zhang, Xiwang Wu, Bingfang Li, Qiangzi Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China

ISBN: (纸本)9780819469502

High-resolution remote sensing image is usually considered that its pixel size is less than 10 meters. Traditional classification methods based on pixels are not fit for the classification of this kind of image because this kind of image has higher spatial resolution and more local heterogeneity compared to the low-resolution remote sensing image data. Object-oriented image classification method provides a good technique to solve this problem. This method segments image to create homogeneous regions or image objects through region merging or boundary detection algorithms. Objects possess more features such as geometric and structure characteristics besides spectral characteristics than pixels. So it is important to select appropriate characterstics in classification. Class-Related features, landscape pattern metrics, geometric attributes of objects, spatial information are very useful characteristics. The paper will pay more attention to the selection and integrative utilization of these features and spectral characteristics, and give several examples to show their performance. (1) If We want to extract a kind of feature which has similar spectral characteristic as the other feature but has a certain positional relationship with a specific feature, at this time, Class-Related features will be very efficacious. (2) Both river and pounds have also similar spectral characteristic, but has different geometric characteristic in the landscape pattern metrics. Synthetically use of the landscape pattern metrics and spectral characteristic will wok well. (3) In the same segmentation scale, the objects from the region with more homogeneity will be bigger than other objects from the region with more heterogeneity. So, the area and spectral characteristic can be used in classification. The results show a better accuracy. The selection and integrative utilization of features of objects were very important in achieving these high accuracies.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Visualization analysis platform based on land surface remote sensing radiation transfer characteristics

Visualization analysis platform based on land surface remote...

引用

conference on pattern recognition and Computer Vision

作者： Wu, Song Liu, Qinhuo Huang, Huaguo Xin, Xiaozhou Chen, Min Univ Elect Sci & Technol China Automat Engn Acad Chengdu 610054 Peoples R China Beijing Normal Univ Inst Remote Sensing Applicat Chineese Acad Sci State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

ISBN: (纸本)9780819469526

We outline a platform for rendering the canopy reflected irradiance under the irradiation of different wavelengths. Our approach is to use different colors to symbol value of canopy reflected irradiance in different ranges. Meanwhile, we do some statistical analysis according to the results above. We illustrate our approach for simple 3-D trees scenes under the irradiation of 6 different wavelengths, respectively in visible light waveband and near infrared waveband. Our results are good. We get the vivid light shadow effect in the representation of 3-D trees scenes. We use 6 colors to represent 6 consecutive canopy reflected irradiance range and make some statistical analysis to get useful information from the results above.

关键词： canopy reflected irradiance 3-D tree scenes wavelengths statistical analysis

来源：评论

学校读者我要写书评

暂无评论

Biometric identification via PCA and ICA based pattern recognition

Biometric identification via PCA and ICA based pattern recog...

引用

IEEE International conference on Control and Automation

作者： Ye, Zhengmao Ye, Yongmao Mohamadian, Habib Southern Univ Dept Elect Engn Baton Rouge LA 70813 USA Liaoning TV Stn Technol Ctr Broadcasting Dept Shenyang 110004 Peoples R China Southern Univ Coll Engn Baton Rouge LA 70813 USA

ISBN: (纸本)9781424408177

Biometric pattern is the unique signature of people. Biometric verification is a very complicated procedure involving technologies of pattern recognition, signal processing and image processing. In most cases it is necessary to employ artificial intelligence based approaches. This work is focused on intelligent control applications on biometric verification. The actual sensing information is digitized into image matrix files and then data matrices are analyzed using advanced algorithms. Thus, the real patterns of fingerprints will be captured. The information is indicated by plaintexts containing inherent signatures. After transforming plaintext data into ciphertext data, each of three RGB intensity components of the trimulus color system is computed and analyzed individually. Then Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are applied for decision making. Its assumption is evident and very effective that biometric fingerprints can be effectively recognized by utilizing advanced artificial intelligence technologies.

关键词： pattern recognition Principal Component Analysis Independent Component Analysis

来源：评论

学校读者我要写书评

暂无评论

Object specific compressed sensing

Object specific compressed sensing

引用

conference on Applications of Digital image processing XXX

作者： Mahalanobis, Abhijit Muise, Robert Martin, Lockheed Missiles & Fire Control Orlando FL 32819 USA

ISBN: (纸本)9780819468444

Compressed sensing holds the promise for radically novel sensors that can perfectly reconstruct images using considerably less samples of data than required by the otherwise general Shannon sampling theorem. In surveillance systems however, it is also desirable to cue regions of the image where objects of interest may exist. Thus in this paper, we are interested in imaging interesting objects in a scene, without necessarily seeking perfect reconstruction of the whole image. We show that our goals are achieved by minimizing a modified L2-norm criterion with good results when the reconstruction of only specific objects is of interest. The method yields a simple closed form analytical solution that does not require iterative processing. Objects can be meaningfully sensed in considerable detail while heavily compressing the scene elsewhere. Essentially, this embeds the object detection and clutter discrimination function in the sensing and imaging process.

关键词： Compressed sensing Reconstruction algorithms image processing image compression pattern recognition Sensors Visualization Chemical elements Surveillance Mahalanobis distance

来源：评论

学校读者我要写书评

暂无评论

Clustering polarimetric SAR image under deorientation theory

Clustering polarimetric SAR image under deorientation theory

引用

32nd IEEE International conference on Acoustics, Speech and Signal processing

作者： Kang, Xin Han, Chongzhao Xu, Feng Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Peoples R China Fudan Univ Minist Educ Res Key Lab Wave Scattering & Remote Sensing Informat Shanghai 200433 Peoples R China

ISBN: (纸本)9781424407286

In natural complex terrain surfaces, scattering targets with random orientations produce random fluctuating echoes which lead to confused classifications by directly using target decomposition on polarimetric SAR (PolSAR) image. In order to reduce the influence, the target vector is transformed into the state with minimization of cross-polarization. Then a set of new parameters u/v/w are used to characterize scattering mechanisms under the deorientation theory, and the fuzzy membership is adopted instead of "hard" division of parameter plan. Characterizing the sample coherency matrices as complex Wishart distribution, the PolSAR image is clustered based on Bayes Maximum Likelihood (ML) criteria. Experiment is carried out on an L-band NASA/JPL SIR-C PolSAR image over Danshui town, Guangdong, China. Comparison results with the popular used methods show that the proposed method provides a significant improvement in classification and the associated scattering mechanism of class is more accurate and beneficial for automatic terrain recognition.

关键词： deorientation pattern classification fuzzy clustering radar polarimetry SAR

来源：评论

学校读者我要写书评

暂无评论

Atmospheric correction algorithm for MODIS data of inland waters by using short-wave infrared bands

Atmospheric correction algorithm for MODIS data of inland wa...

引用

5th International Symposium on Multispectral image processing and pattern recognition

作者： Li, Junsheng Zhang, Bing Shen, Qian Zhang, Xia Chen, Zhengchao Chinese Acad Sci Inst Remote Sensing Applicat State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

ISBN: (纸本)9780819469519

Atmospheric correction, which can retrieve water-leaving radiance, is an important preprocess in monitoring water quality from remote sensing data. The atmospheric correction algorithms developed by Gordon (1993, 1994) assume that water-leaving radiance of ocean waters in near infrared is zero. However, such an assumption is not applicable to inland waters, and usually leads to failure in atmospheric correction of remote sensing data of inland waters. Some scientists, based on some other assumptions, have developed some improved atmospheric correction algorithms which can be applied to coastal and inland waters. However, these algorithms can only get good results in specific areas. In order to get good results of atmospheric correction of remote sensing data of inland waters in China, an improved atmospheric correction algorithm is developed in this paper. This improved atmospheric correction algorithm assumes that water-leaving radiance in short-wave infrared is zero, which is based on the analysis of absorption and scattering characteristics of inland waters. This atmospheric correction algorithm is validated to have high applicable potentials by applied to concurrent MODIS data and in-situ measured reflectance spectra in Guanting Reservoir in North China.

关键词： MODIS atmospheric correction inland waters water-leaving radiance short-wave infrared

来源：评论

学校读者我要写书评

暂无评论

Residual-scaled local standard deviations method for estimating noise in hyperspectral images - art. no. 678713

Residual-scaled local standard deviations method for estimat...

引用

5th International Symposium on Multispectral image processing and pattern recognition

作者： Gao, Lianru Zhang, Bing Wen, Ranting Ran, Qiong Chinese Acad Sci Inst Remote Sensing Applicat State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

ISBN: (纸本)9780819469519

A new method for estimating noise in hyperspectral images is described in this paper. It is based on the strong between-band correlation of hyperspectral images and the concept of local standard deviations of small imaging blocks. The new method can be used to automatically estimate noise for both radiance and reflectance images. Unlike other methods discussed in this paper, the new method is more reliable for estimating noise in hyperspectral images with diverse land cover types. We successfully applied the new method in estimating noise for Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data.

关键词： hyperspectral image noise multiple linear regression residual local standard deviation

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：