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检索条件"任意字段=MIPPR 2007: Multispectral Image Processing"

共 197 条记录，以下是61-70 订阅

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Auto-segmentation based on graphcut and template

Auto-segmentation based on graphcut and template

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Zhang, Hong Zuo, Wei Mu, Ying Beihang Univ Image Proc Ctr Beijing 100083 Peoples R China

ISBN: (纸本)9780819469502

In this paper, the main idea is to use the prior knowledge to guide the segmentation. Firstly the continuity among adjacent frames is used to create a motion template according to the Displaced Frame Difference's (DFD) higher character([1]). And then the color template is established by using the k-means clustering. Based upon the information derived from the previous two templates, the segmentation image is defined as foreground, background and boundary regions. Then, the segmentation problem is formulated as an energy minimization problem. The hard edge of foreground is then obtained by implementing graph-cut algorithm. Experimental results demonstrate the effectiveness of proposed algorithm.

关键词： automatic video segmentation graph-cut algorithm video object template

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image inpainting under different displacement view images

Image inpainting under different displacement view images

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5th International Symposium on multispectral image processing and Pattern Recognition

作者： Ma, Wenjuan Hu, Maolin Anhui Univ Lab Intelligent Comp & Signal Proc Hefei 230039 Anhui Peoples R China

ISBN: (纸本)9780819469502

In this paper, image inpainting based on different displacement view images is proposed, which is the problem of filling in the occluded or damaged regions of an image by the visible information from other different displacement view images. The key problems are how to convert the visible information in different displacement view images to consistence and to use available information to repair the target image. The first step of our method is to divide all images into different scene planar regions and to transform all image regions into current view by projective transformation computed from the matched points;thus the visible information can be directly used, then a new inpainting algorithm based on image fusion with spatial frequency is applied. The experiment shows good and harmonious results for the repaired image.

关键词： image inpainting different displacement view images image fusion

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IR scene image generation from visual image based on thermal database

IR scene image generation from visual image based on thermal...

引用

mippr 2007: multispectral image processing

作者： Liao, Binbin Wang, Zhangye Ke, Xiaodi Xia, Yibin Peng, Qunsheng State Key Laboratory of CAD and CG Zhejiang University 388 Yuhangtang Road Hangzhou 310058 China

ISBN: (纸本)9780819469519

In this paper, we propose a new method to generate complex IR scene image directly from the corresponding visual scene image based on material thermal database. For the input visual scene image, we realize an interactive tool based on the combined method of global magic wand and intelligent scissors to segment the object areas in the scene. And the thermal attributes are assigned to each object area from the thermal database of materials. By adopting the scene infrared signature model based on infrared Physics and Heat Transfer, the surface temperature distribution of the scene are calculated and the corresponding grayscale of each area in IR image is determined by our transformation rule. We also propose a pixel-based RGB spacial similarity model to determine the mixture grayscales of residual area in the scene image. To realistically simulate the IR scene, we develop an IR imager blur model considering the effect of different resolving power of visual and thermal imagers, IR atmospheric noise and the modulation transfer function of thermal imager. Finally, IR scene images at different intervals under different weather conditions are generated. Compared with real IR scene images, our simulated results are quite satisfactory and effective.

关键词： Infrared imaging

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Robust L1 PCA and application in image denoising

Robust L1 PCA and application in image denoising

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Gao, Junbin Kwan, Paul W. H. Guo, Yi Charles Sturt Univ Sch Comp Sci Bathurst NSW 2795 Australia Univ New England Sch Sci & Technol Armidale NSW 2351 Australia

ISBN: (纸本)9780819469502

The so-called robust L1 PCA was introduced in our recent work [1] based on the L1 noise assumption. Due to the heavy tail characteristics of the L1 distribution, the proposed model has been proved much more robust against data outliers. In this paper, we further demonstrate how the learned robust L1 PCA model can be used to denoise image data.

关键词： robust L1 PCA Bayesian learning denoising

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Hyperspectral data classification using image fusion based on curvelet transform

Hyperspectral data classification using image fusion based o...

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Sun, Airong Tan, Yihua Wuhan Inst Technol Sch Engn & Comp Sci Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sate Key Lab Multispectral Informat Proc Technol Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469519

A new supervised classifier based on image fusion of hyperspectral data is proposed. The technique first selects the suitable bands as the candidates for fusion. Then, the bands based on curvelet transform are fused into several components. The fused hyperspectral components as the extracted features are fed into the supervised classifier based on Gaussian Mixture Model. After the estimation of the GMM with Expectation Maximization, the pixels are classified based on the Bayesian decision rule. One requirement of the technique is that the training samples should be provided from the hyperspectral data to be analyzed. The main merits of the new method contain tow folds. One is the novel feature extraction based on curvelet transform which fully makes use of the spectral properties of the hyperspectral data. The other one is the low computing complexity by reducing the data dimension significantly. Experimental result on the real hyperspectral data demonstrate that the proposed technique is practically useful and posses encouraging advantages.

关键词： hyperspectral data curvelet transform fusion classification

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Algorithm of optical remote sensing image registration based on strong edge region

Algorithm of optical remote sensing image registration based...

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5th International Symposium on multispectral image processing and Pattern Recognition

作者： Yao, Ting Yin, Dong Liu, Yuan Univ Sci & Technol China Dept Elect Eng & Informat Sci Hefei 230027 Anhui Peoples R China

ISBN: (纸本)9780819469502

Aiming at the registration of optical remote sensing images, an algorithm based on strong edge region is proposed. First, the strong edge regions are extracted. Then combines with the regions' moment invariants and RANSAC method, it can obtain an accurate match of the strong edge regions. Utilizing the centroids of the matching regions as control points in the affine geometric distortion, an automatic registration is performed. A large number of experiments are fulfilled with SPOT and Quickbird satellite images and good results are obtained.

关键词： Strong Edge Region moment invariants random sample consensus (RANSAC) image registration affine transformation

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

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

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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

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IR image generation of space target based on openGL

IR image generation of space target based on openGL

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5th International Symposium on multispectral image processing and Pattern Recognition

作者： Shen, Tongsheng Guo, Ming Wang, Chenggang Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Naval Aeronaut Engn Inst Dept Control Engn Yantai 264001 Shandong Peoples R China

ISBN: (纸本)9780819469502

IR Scene simulation has been an important way to design and assess the IR sensor, and the key of simulation is the generation of IR scene image. Based on OpenGL, the method of IR image generation is proposed. The geometry model is constructed with professional CAD software, and the observer location is determined after scene transformation. The full infrared model of space target is built based on infrared physics and heat transfer, which includes the radiation, convection, conduction between different parts of the space target, and which also includes the radiation, convection of environment. Radiance of space target is converted to gray value, and properties of scene are defined according to the gray level. After a series of processing, dynamic IR images are generated with the technology of double buffering.

关键词： OpenGL space target IR radiation quantization IR imaging simulation

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Novel feature extraction method for hyperspectral remote sensing image

Novel feature extraction method for hyperspectral remote sen...

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Liu, Chunhong Zhao, Huijie Beijing Univ Aeronaut & Astronaut Sch Instrument Sci & Optoelect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9780819469519

In order to reduce high dimensions of hyperspectral remote sensing image and concentrate optimal information to reduced bands, this paper proposed a new method of feature extraction. The new method has two steps. The first step is to reduce the high dimensions by selecting high informative and low correlative bands according to the indexes calculated by a smart band selection method. The criterions that SBS method complied are: (1) The selected bands have the most information;(2) The selected bands have the smallest correlation with other bands. The second step is to decompose the selected bands by a novel second generation wavelet, predicting and updating subimages on rectangle and quincunx grids by Neville filters, finally using variance weighting as fusion weight. A 126-band HYMAP hyperspectral data was experimented in order to test the effect of the new method. The results showed classification accuracy is increased by using the novel feature extraction method.

关键词： hyperspectral remote sensing image smart band selection second generation wavelet fusion classification

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Target trace acquisition method in serial star images of moving background

Target trace acquisition method in serial star images of mov...

引用

mippr 2007: Automatic Target Recognition and image Analysis;and multispectral image Acquisition

作者： Chen, Biao Zhang, Chunhua Zhou, Xiaodong Navy Submarine Academy Qingdao 266000 China Naval Aeronautical Engineering Institute NAEI Yantai 264001 China

ISBN: (纸本)9780819469502

The paper put forward a small target trace acquisition algorithm in serial star images of moving background, For the CCD serial star images, while the space target is moving, the background is still moving because of the CCD flat is moving, At the same time, because of dithering of CCD flat and some other reasons, the gray value of target is not invariable, so much as to disappear in the background noise, The algorithm can detect the discontinuous trace of small space target with high accuracy, Originally, the K-sigma cross projection method is used in background star and target area acquisition, Then, a group of N brightest stars in every image is used to estimate the moving vector of the whole background, Finally, a target trace acquisition method is put forward, The simulation experiment is done with two small targets in 16 frame serial star images, and results of trace acquisition show that the algorithm can detect traces of the two targets with high accuracy.

关键词： image acquisition

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