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检索条件"任意字段=MIPPR 2007: Automatic Target Recognition and Image Analysis;and Multispectral Image Acquisition"

共 165 条记录，以下是61-70 订阅

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Automated airport targets detection and location based on radar imagery

Automated airport targets detection and location based on ra...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Shao, Yongshe Chen, Ying Li, Jing Tongji Univ Survey Dept 1239 Si Ping Rd Shanghai 200092 Peoples R China Xian Res Inst Surveying & Mapping Xian 710002 Peoples R China

ISBN: (纸本)9780819469502

Because of the influence of speckle noise, it is difficult to extract the edge of the targets and locate the airport automatically in the low SNR real aperture radar imagery by the traditional ways. The paper presents a kind of algorithms that could improve the dependability of the image matching and locate the airport target in the real aperture radar images. At first, the original real aperture radar imagery is enhanced on fuzzy property domain, which makes the airport target more prominent. Then, the airport runway is detected using the Radon transform, and the end points and width of the airport runway are identified using the correlative knowledge of the airport. At last, the airport runway extracted is processed and the airport target is located with the wavelet transform and the least square image matching. The experiment shows that the method could detect and locate the airport target well.

关键词： real aperture radar image Synthetical aperture radar image Radon transform Fuzzy domain image matching and location

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SAR image segmentation with level set and clonal selection algorithm

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

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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 using improved adaptive proportion-shrinking algorithm based on second generation bandelets

Image denoising using improved adaptive proportion-shrinking...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Hou, Biao Li, Haigang Jiao, Licheng Feng, Hongxiao Xidian Univ Inst Intelligent Informat Proc Xian Peoples R China

ISBN: (纸本)9780819469502

As one important multiresoltion geometry analysis tool, second generation bandelets can make full use of intrinsic geometry regularity of images, and then produces a sparse representation. This paper proposes a new denoising method, which is based on second generation bandelets and improved adaptive proportion-shrinking algorithm. Experiments on natural images with additive Gaussian white noise show that our method not only has the high peak signal to noise ratio(PSNR) value but also has finer impression in vision, especially, has better performance on preservation of edges information and textures information than the classical proportion-shriking algorithm.

关键词： image denoising wavelet transforms second generation bandelets proportion-shrinking algorithm window-based interpolation

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Study on edge extraction methods of the droplet image profile

Study on edge extraction methods of the droplet image profil...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Song, Qing Zhu, Sijia Yan, Han Wu, Wenqian Beijing Univ Posts & Telecommun Automat Sch Beijing 100876 Peoples R China

ISBN: (纸本)9780819469502

It is a key technology to detect the edge of the droplet profile exactly for application in drop volume calculation, liquid target identification and liquid characteristics analysis. The droplet images in various stages during the drop growth are firstly acquired and stored real-timely through ICCD. After a series of preprocessing, including image cutting, noise filtering, image segmentation and filling, a proper edge detection method is chosen to extract the droplet image profile. The principle and algorithm of some classical and newly developed methods for edge detection are introduced and compared in detail, such as differential operator, Laplacian operator, improved Canny operator, wavelet transformation, mathematical morphology, fuzzy operator and fractal geometry. Wavelet transformation can be used effectively for extracting the droplet image profile, because of its advantages of multiple resolution, focus variation and edge enhancement. The image records of the droplet formation and the detected profile curves are presented.

关键词： edge extraction image process droplet profile

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Infrared small target detection and tracking under the conditions of dim target intensity and clutter background

Infrared small target detection and tracking under the condi...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Bai, Xiangzhi Zhou, Fugen Jin, Ting Xie, Yongchun Beihang Univ Image Proc Ctr Beijing 100083 Peoples R China Beijing Inst Control Engn Beijing 100080 Peoples R China

ISBN: (纸本)9780819469502

To reduce the influences of the dim target intensity and heavy clutter on infrared small target detection and tracking, a novel algorithm is presented in this paper. The algorithm proposes a modified top-hat transformation by importing the property of the small target region firstly, which largely enhances the dim target and apparently suppresses the heavy clutter. Consequently, the potential targets are easy to be segmented by the iterative thresholding method. After decreasing the false alarms through the dilation cumulation, the real target and the trajectory are correctly given by using the data association formed by the motion property of the real target. Various experiments verified that the proposed algorithm was efficient and robust for dim target detection and tracking under the condition of heavy clutter.

关键词： target detection and tracking infrared dim small target clutter background top-hat transformation dilation cumulation iterative thresholding

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Light-Microscopic image restoration via edge detection

Light-Microscopic image restoration via edge detection

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Sun, Mingzhu Zhao, Xin Lu, Guizhang Nankai Univ Org Inst Robot & Automat Informat Syst Tianjin 300071 Peoples R China

ISBN: (纸本)9780819469502

A semi-blind image restoration approach is put forward in this paper for light-microscopy system. Microscope creates unavoidable light artefacts because of the Point Spread Function (PSF) of the optical system, and our early research shows that PSF of the microscopy system can be modeled as isotropic Gaussian blur. That is the motivation of this paper. We present an algorithm, based on functional minimization, which integrates Canny edge detection with semi-blind deconvolution. An alternating minimization (AM) implicit iterative scheme is devised to recover the image and simultaneously identify PSF. Good performance is observed with numerically blurred images and really microscopic images, even under the presence of high noise level.

关键词： semi-blind deconvolution microscopic image restoration edge detection anisotropic smoothness AM Algorithm

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Improved clustering algorithm for image segmentation based on CSA

Improved clustering algorithm for image segmentation based o...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Zhang, Xiaohua Yang, Pu Jiao, Licheng Hou, Xiaojin Xidian Univ Inst Intelligent Informat Proc Xian 710071 Peoples R China

ISBN: (纸本)9780819469502

image segmentation is the prerequisite step for further image analysis. Segmentation algorithms based on clustering attract more and more attentions. In this paper, an image-domain based clustering method for segmentation, called CSA-CA, is proposed. In this method, a scale parameter is introduced instead of an apriori known number of clusters. Considering that adjacent pixels are generally not independent of each other, the spatial local context is took account into our method. A spatial information term is added so that the near pixels have higher probability to merge into one cluster. Additionally, a clonal selection clustering operator is used so that a cluster is capable of exploring the others that are not neighboring in spatial but similar in feature. In the experiments we show the effectiveness of the proposed method and compare it to other segmentation algorithms.

关键词： image segmentation clustering algorithm image domain clonal selection algorithm

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ISAR image Visualization for Aerospace targets 11

ISAR Image Visualization for Aerospace Targets

引用

11th International Symposium on multispectral image Processing and Pattern recognition (mippr) - multispectral image acquisition, Processing, and analysis (mippr)

作者： Liu, Yang Li, Gang SHi, Si Zhang, Chi Li, Bingning Xian Satellite Control Ctr Xian 710043 Shaanxi Peoples R China 31011 Troops PLA Beijing Peoples R China

ISBN: (纸本)9781510636347

Due to the large dynamic range and low contrast, inverse synthetic aperture radar (ISAR) image is not appropriate for human observation. In order to output and display the target imaging results, a procedure which compresses the dynamic range of the raw images into a lower range is necessary. In this paper, by analyzing the histogram of original ISAR images, the characteristics of ISAR images are investigated. Given the sparse amplitude distribution of original ISAR image and the shortcomings existing in the sparse linear histogram, this paper proposes an ISAR image detail enhancement algorithm (ISARIDE) based on histogram equalization and dynamic range compression. The advantage of the proposed method is that it can retain the target structure infounation, and improve the visual effect of human eye to target details as soon as possible. The proposed algorithm was tested on the simulated data and real data. The selected target is a flying Boeing *** results show the validity of the algorithm.

关键词： inverse synthetic aperture radar (ISAR) dynamic range compression (DRC) image detail enhancement visualization aerospace targets

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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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Adaptive wiener filter based on wavelet transform

Adaptive wiener filter based on wavelet transform

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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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