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检索条件"任意字段=5th International Symposium on Multispectral Image Processing and Pattern Recognition"

共 1596 条记录，以下是81-90 订阅

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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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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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Linear object extraction from high-resolution image based on MRF and Bayesian

Linear object extraction from high-resolution image based on...

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5th international symposium on multispectral image processing and pattern recognition

作者： Yu, Changhui Meng, Lingkui Yi, Yaohua Yang, Zhigao Wuhan Univ Sch Remote Sensing Informat Engn 129 Luoyu Rd Wuhan 430079 Peoples R China Wuhan Univ Sch Printing & Packaging Wuhan AH-430079 Peoples R China Wuhan Univ State Key Lab Informat Engn Surveying Mapping & Remote Sensing Wuhan AH-430079 Peoples R China

ISBN: (纸本)9780819469502

the commercialization of high resolution remote sensing image provides the image application more widely space. How to extract the interested important objects quickly and exactly from remote sensing image is always the research focus. After analyzed the characteristics of road in high resolution image, the paper constructed the road extraction model based on MRF and Bayesian. And finally the validity of the method was confirmed by an example.

关键词： high resolution remote sensing image bayesian markov random field

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Facet-based adaptive anisotropic diffusion for image selective smoothing

Facet-based adaptive anisotropic diffusion for image selecti...

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5th international symposium on multispectral image processing and pattern recognition

作者： Wang, Guodong Sang, Nong Yan, Luxin Shen, Xubang Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence State Key Lab Multi Spectral Informat Proc Techno Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469502

In each step of anisotropic diffusion smoothing, noises must be managed to get better results. the mostly used method is Gaussian filtering. However, the standard deviation of the Gaussian filter can't be accurately obtained and it should change during the iterative process. Another problem is how to select a proper standard deviation to reducing noises while preserving edges. Actually, facet model fitting can be taken as a natural way to overcome the drawbacks mentioned above. Facet model fitting has the low-pass filtering performance adaptive to the image during evolution of diffusion;it can also achieve balanced results for noise reduction and edge preserving. Experiments show the method can preserve more edges as well as obtain higher peak signal-to-noise ratio as compared to other anisotropic diffusion based selective smoothing approaches.

关键词： facet-model image selective smoothing anisotropic diffusion

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

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

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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

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image denoising with window shrink wavelet coefficients by adaptive threshold - art. no. 678613

Image denoising with window shrink wavelet coefficients by a...

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5th international symposium on multispectral image processing and pattern recognition

作者： Zhao, Yifan Li, Jiuxian Xia, Liangzheng SE Univ Dept Automat Control Nanjing 210096 Peoples R China

ISBN: (纸本)9780819469502

We introduce an adaptive wavelet coefficients shrinkage method and apply it to image denoising. Donoho's denoising scheme which is based on thresholding the wavelet coefficients, eliminates too many wavelet coefficient without considering the image's local characteristics. In this paper we propose a new shrinkage method which can modify the magnitude of shrinkage by considering neighboring wavelet coefficients and variance of noise. So we can use more wavelet decomposition levels than other wavelet shrinkage methods to recover the noisy images. the proposed method outperforms the other methods given in literature, while its implementation and concept are both simple.

关键词： wavelet shrinkage image denoising adaptive threshold neighboring coefficients

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Method to reduce over-segmentation of images using immune clonal algorithm - art. no. 678649

Method to reduce over-segmentation of images using immune cl...

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5th international symposium on multispectral image processing and pattern recognition

作者： Liang, Jianhua Wang, Shuang Jiao, Licheng Xidian Univ Inst Intelligent Informat Proc Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)9780819469502

image segmentation is a difficult task. these years, researchers have proposed many segmentation methods based on Evolutionary Algorithms, but most of them used Evolutionary Algorithms to optimize the parameters of an existing segmentation algorithm. this paper tries to use the Evolutionary Algorithms to segment images expecting to explore a new way of image segmentation. the method described in the paper pre-segments the image by Watersheds and then merges it by Immune Clonal Algorithm (ICA). To implement the task, several operators are proposed such as the DC operator, the Proportional Creation of the First generation operator, and fitness function based on JND and average gray value. In the end, the proposed method is compared with another method using GA. the experiments show that the method is effective and the work is significant.

关键词： image segmentation over-segmentation evolutionary algorithm immune clonal algorithm

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Moving point target detection using temporal variance filter in IR imagery

Moving point target detection using temporal variance filter...

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5th international symposium on multispectral image processing and pattern recognition

作者： Sun, Xiechang Zhang, Tianxu Li, Meng Huazhong Univ Sci & Technol State Key Lab Multispectral Informat Proc Technol Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469502

A crucial problem in Infrared Search and Track (IRST) systems is the detection of moving point targets, there are many algorithms reported in the literature for dealing with this problem, yet none of them yield acceptable results under all situations. In this paper, we describe a new temporal variance filter (TVF) for detecting targets whose velocity are higher than 1 pixel/frame;the filter iteratively estimates the temporal variance of each pixel, then subtracts the last iteration step variance from the variance of current step. Subsequently, we introduce a novel image segmentation algorithm in order to extract point targets from clutter background, the trajectories of the point targets could be established by post-processing algorithm. Before applying the temporal filter, the anti max-median filter given by Suyog D. Deshpande et al. is incorporated as a preprocessing technique to suppress cloud clutter. It is assumed that targets' velocity is higher than 1 pixel/frame;targets with sub-pixel/frame velocity are not considered. the performance of our approach is evaluated by using available real-world infrared image sequences containing simulated moving point targets;it performs steadily under most situations.

关键词： point target detection temporal variance filter noise rejection image segmentation visual contrast IR imagery

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Color image segmentation by integrating texture measure into JSEG method

Color image segmentation by integrating texture measure into...

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5th international symposium on multispectral image processing and pattern recognition

作者： Sheng, Qinghong Zhang, Jianqing Xiao, Hui Wuhan Univ Inst Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)9780819469502

We present a new color image segmentation method that combined texture measures and the JSEG (J measure based JSEGmentation) algorithm. In particular, two major contributions are set forth in this paper. (1) the two measures defined in JSEG and the Laws texture energy is discussed respectively and then we find that the over-segmentation problem of JSEG could be attributed partly to the absence of color discontinuity in the J measure. (2) A new measure is proposed by integrating the Laws texture energy measures into the J measure, on which our segmentation method is based. the new segmentation method taking account of both textural homogeneity and color discontinuity in local regions can be used to detect proper edges at the boundaries of shadows and highlights. Performance improvement due to the proposed modification was demonstrated on a variety of real color images.

关键词： color image segmentation JSEG Laws texture energy homogeneity measure

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Adaptive recursive algorithm for infrared ship image segmentation based on gray-level histogram analysis

Adaptive recursive algorithm for infrared ship image segment...

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5th international symposium on multispectral image processing and pattern recognition

作者： Wang, Xinyu Xu, Huosheng Wang, Heng Wuhan Digital Engn Inst Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469502

the infrared ship segmentation in digital images is a fundamental step in the process of ship recognition. this paper presents an adaptive recursive algorithm for infrared ship image segmentation based on the gray-level histogram analysis of the image. the proposed algorithm consists of four phases. First, the gray-level histogram of the image is generated and de-noised by using wavelets transform. Second, a threshold level which best extracts the ship from the water region is selected according to the histogram profile analysis. third, the rationality of the selected threshold is analyzed based on the prior information about infrared ship images. If the selected threshold is not reasonable, we can still use it as the recursive initial threshold and the infrared ship image will be further segmented with a local recursive method based on the method proposed by OTSU until it reaches the prescriptive termination criteria. Finally, we eliminate the spurious pixels by extracting the greatest connected region and filling the holes. the segmentation algorithm works successfully for classification of infrared ships, and some experimental results are also presented.

关键词： image segmentation ship classification target infrared

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