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共 197 条记录，以下是81-90 订阅

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Adaptive fused Kalman filter based on imaging laser radar for TAN

Adaptive fused Kalman filter based on imaging laser radar fo...

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Gong, Junbin Xu, Hongbo Tian, Jinwen Cheng, Hua Zhang, Jun Huazhong Univ Sci & Technol State Key Lab Multispectral Informat Proc Technol Wuhan 430074 Peoples R China Huazhong Normal Univ Dept Phys Wuhan 430079 Turkey

ISBN: (纸本)9780819469519

Terrain aided navigation (TAN) is an efficient way to periodically correct the error accumulation of INS. The imaging laser radar is an ideal imaging sensor in TAN for the low-flying aircraft and unmanned air vehicles for the high precision multi-dimensional data acquisition capability and concealable attribute. In this paper, a new framework for applying the laser radar to terrain aided navigation is put forward. Then a new adaptive fused Kalman Filter is proposed to improve the accuracy and robustness. At last, the key factors affected the algorithm are analyzed and the comparative experimentations are presented. The simulating experiments show that the proposed algorithm improves the location accuracy. and has good initial error tolerance and fine robustness. It shows that this approach is a valid solution for the application.

关键词： adaptive fused Kalman filter terrain aided navigation imaging laser radar 3D terrain matching

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Effective method to evaluate the complex degree of sea-sky infrared backgrounds

Effective method to evaluate the complex degree of sea-sky i...

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Gao, Chenqiang Tian, Jinwen Wang, Zhicheng Wang, Yongtao Wang, Peng Huazhong Univ Sci & Technol State Key Lab Multispectral Informat Proc Technol Wuhan 430074 Peoples R China Tongji Univ Res Ctr CAD Shanghai 200092 Peoples R China

ISBN: (纸本)9780819469519

When designing the system of the infrared (IR) small target detection, both which detection algorithm to be chosen and how to set some parameters of the detection algorithm need to evaluate the complexity of the infrared backgrounds. In this paper, an effective method to evaluate the complexity of the sea-sky infrared backgrounds based on texture analysis is proposed. According to the characteristics of Infrared backgrounds, three statistical descriptors based on gray level co-occurrence matrix are calculated, and one statistical descriptors based on edge information is calculated. All statistical descriptors are fused to evaluate the complexity of IR backgrounds finally. Real and synthetic IR images under sea-sky background are applied to validate the proposed approach. Compared to existing methods, Experimental results demonstrate the robustness of the proposed method with high performance.

关键词： infrared background complexity contrast entropy moment edge information

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Multi-focus image fusion using adaptive Wiener filter

Multi-focus image fusion using adaptive Wiener filter

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5th International Symposium on multispectral image processing and Pattern Recognition

作者： Hu, Junhong Zhang, Tianxu Zhong, Sheng Chen, Xujun Huazhong Normal Univ Elect & Informat Engn Dept Wuhan Peoples R China Huazhong Univ Sci & Technol Inst Pattern Recognit & AI Wuhan Peoples R China

ISBN: (纸本)9780819469502

This paper presents a new method for multi-focus image fusion. In the method, the source images are first decomposed into blocks, and the decomposed images are then combined by the use of adaptive Wiener filter. Effects of the block size and threshold are analyzed, and comparison with wavelet transform based method is done. Experimental results show that the proposed method is comparative to wavelet transform based methods for the images without noise, while this method is computationally simpler, and can be implemented in real-time applications. Experimental results also show that under noise circumstances, additive noise or multiplicative noise, the proposed method is obviously superior to the wavelet based method.

关键词： multi-focus Wiener filter image fusion

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Blind image restoration based on a new wavelet edge detection

Blind image restoration based on a new wavelet edge detectio...

引用

mippr 2007: multispectral image processing

作者： Hongzhi, Wang Jinying, Guo Lili, Liu Institute of Computer Science and Engineering Changchun University of Technology Changchun University of Technology

ISBN: (纸本)9780819469519

We present an effective image recovering method. Edge information are very important, we can detect the edge of the image via wavelet transform before recovering the image. In this paper, we give a simple and effective method to detect the edge information. The first, we can decompose the image using a wavelet transform, the high frequency information is corresponding to the edge and noise, the edge and noise have different properties, as follows: the orientation of edge is very strong, but the noise is non-orientation. On base of that, we can decompose the edge and noise in horizontal orientation, vertical orientation, and diagonal orientation. Because the edge is directional, its values in each orientation have much difference;in opposition, noise is non-orientation, its values are almost same. We can set the threshold based on the variances of difference in each orientation. By this time, we gain the edge without noise. For the rest, we can restore using regularization. Now the low frequency is corresponding to the flat. In this paper, we detect the edge by the wavelet, so can choose a bigger parameter to recover. At last, we add the edge and the part of regularized image restoration. This method has advantage in holding the edge and is simple to choose the parameter of regularization. Experimental results show the good performance, this method can keep image's of edge from degradation and increase PSNR up to 1-2dB.

关键词： image reconstruction

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Adaptive wiener filter based on wavelet transform

Adaptive wiener filter based on wavelet transform

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Bai, Wenruo Zhang, Baofeng Bai, Qianqian Tianjin Univ Technol 263 Hongqinan Rd Tianjin 300191 Peoples R China Tianjin Inst Urban Construct Tianjin 300384 Peoples R China

ISBN: (纸本)9780819469502

This paper presents a new method for image filtering process, an adaptive Wiener filter, which is based on wavelet transform. The filter provided uses threshold mode filtering as its precursor. The pertinence between wavelet coefficients is taken into consideration in the process of determining the threshold quantities, which makes the filter adaptive. The result of the threshold mode filter is then processed by Wiener filtering model. The whole image filtering system is composed of threshold mode filtering based on wavelet transform as well as Wiener filtering technique. What's more, the performance is also an important subject. And it gives a better smooth filtering result.

关键词： image filtering adaptive filter Wiener wavelet transform

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SAR image segmentation with level set and clonal selection algorithm

SAR image segmentation with level set and clonal selection a...

引用

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

作者： Hou, Xiaojin Wang, Shuang Jiao, Licheng Xu, Jing Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819469502

Synthetic aperture radar (SAR) image segmentation is a fundamental problem in SAR image interpretation. SAR images often contain non-texture object and texture object. Level set method, known as deformable model, is a powerful image segmentation technique. It can get accurate contours of non-texture object, but has poor performance in getting contours of texture object. In this paper, a new modified model of level set based on clonal selection algorithm is proposed. We use clonal selection algorithm to choose some pixels near the contour, and then perform a neighborhood modification on the level set function during its evolution. The region texture information, supervising the modification process, is incorporated into the level set framework. This new method is particularly well adapted to detection of texture object of interesting. We illustrated the performance of the new method on SAR images. Furthermore, we compared our method with level set method and the modified model of level set based on standard genetic algorithm (SGA) in texture object detection results and image segmentation results. The experimental results show that incorporating region texture information into the level set framework, consistent texture objects are obtained, and accurate and robust segmentations can be achieved.

关键词： image segmentation

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image denoising based on local adaptive multi-scale wavelet least squares support vector regression(MWLS_SVR)

Image denoising based on local adaptive multi-scale wavelet ...

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Wu, Dingxue Peng, Daiqiang Tian, Jinwen Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9780819469502

Rather than attempting to separate signal from noise in the spatial domain, it is often advantageous to work in a transform domain. Building on previous work, a novel denoising method based on local adaptive multi-scale wavelet least squares support vector regression is proposed. Investigation on real images contaminated by Gaussian noise has demonstrated that the proposed method can achieve an acceptable trade off between the noise removal and smoothing of the edges and details.

关键词： multi-scale wavelet least square support vector machines image denoising

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Interactive dynamic graph cut based image segmentation with shape priors

Interactive dynamic graph cut based image segmentation with ...

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5th International Symposium on multispectral image processing and Pattern Recognition

作者： Liu, Chen Li, Fengxia Zhan, Shouyi Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China

ISBN: (纸本)9780819469502

In this paper, we present a new method bases on dynamic graph cut and captures both the shape and the nature information of the image for interactive image segmentation. While traditional interactive graph cut approaches for image segmentation are often successful, they may fail in camouflage. Prior shape knowledge can largely mitigate this problem. In this paper, two kinds of shape priors are taken into account to obtain more accurate results. In order to use the information from user input more effectively, a weight function is introduced to control the relative importance of shape knowledge. Then, a one-shot fully dynamic graph cut algorithm is introduced to minimize the energy function, and during this procedure, only a subset of pixels in the image is considered, which greatly reduces the complexity of dynamic graph cut algorithm. Extensive experiments, including comparisons with some state-of-the-arts, show the effectiveness of our methods in improving the segmentation performance and saving the processing time.

关键词： image segmentation shape prior dynamic graph cut

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Application and comparison of resolving methods in SAR image ortho-rectification based on *** model - art. no. 67871P

Application and comparison of resolving methods in SAR image...

引用

5th International Symposium on multispectral image processing and Pattern Recognition

作者： Yang, Bo Wang, Chao Zhang, Hong Zhang, Bo CAS China Remote Sensing Satellite Ground Stn Beijing 100086 Peoples R China

ISBN: (纸本)9780819469519

In this paper *** model is first realized by programming to accomplish SAR image ortho-rectification, in order to validate the feasibility of this model. Then, for calculating exterior orientation elements of satellites, this paper uses some different solution methods such as Singular Value Decomposition (SVD), Ridge Estimate (RE), Generalized Ridge Estimate (GRE), Linear elements and Angle elements Detaching arithmetic (LAD) and so on, and compares them in iteration stability, convergence rate and result precision. Some primary conclusions are summarized at last.

关键词： SAR image ortho-rectification collinearity equation G.Konecny model exterior orientation elements solution method iteration threshold convergence precision

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Infrared image pre-processing based on nonsubsampled contourlet transform

Infrared image pre-processing based on nonsubsampled contour...

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5th International Symposium on multispectral image processing and Pattern Recognition

作者： Li, Junshan Zhang, Xiongmei Li, Kun Li, Xuhui Inst High Tech Hongqing Town Xian 710025 Peoples R China Xidian Univ Inst Intelligent Informat Proc Xian 710025 Peoples R China

ISBN: (纸本)9780819469519

Based on the nonsubsampled contourlet transform (NSCT) and two denoising models (i.e., fractional power model and cross-scale correlation model), an efficient pre-processing algorithm for infrared image is proposed. In our algorithm, the NSCT is used to decompose the image at different scale and orientation, and then implement pre-processing in the frequency domain. at last reconstruct coefficients to obtain ideal infrared image. The key of the proposed algorithm is pre-processing which includes noise removal and information enhancement. To reduce the two kinds of noises (i.e., Gaussian noise and shot noise) efficiently., the two models referred are applied to the NSCT coefficients respectively. The filtered results are fused to learn from the strong points of each denoising methods to offset the weakness of each other. Later. the denoised coefficients are classified to edges and noise and modified by a nonlinear mapping function. Experiments carried on infrared images show that the new algorithm can reduce the Gaussian noise and shot noise efficiently, while keeping the detail information well. Both in the objective performance index and subjective viewing assessment, the new algorithm is superior to the DWT-based method as well as the traditional method.

关键词： IR nonsubsampled contourlet transform (NSCT) fractional power model image denoising image enhancement Gaussian noise shot noise

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