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

共 1067 条记录，以下是161-170 订阅

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Polarimetric SAR image Classification Based on Discriminative Dictionary Learning Model 10

Polarimetric SAR Image Classification Based on Discriminativ...

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： Sang, Cheng Wei Sun, Hong Wuhan Univ Sch Elect Informat Wuhan 430072 Hubei Peoples R China Telecom ParisTech 46 Rue Barrault F-75013 Paris France

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

Polarimetric SAR (Po1SAR) image classification is one of the important applications of Po1SAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in Po1SAR image classification, however for Po1SAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for Po1SAR classification.

关键词： Polarimetric SAR image classification overcomplete dictionary sparse representation

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A Block-Based JPEG-LS Compression Technique with Lossless Region of Interest 10

A Block-Based JPEG-LS Compression Technique with Lossless Re...

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Parallel processing of images and Optimization Techniques;and Medical Imaging

作者： Deng, Lihua Huang, Zhenghua Yao, Shoukui Huazhong Univ Sci & Technol Sch Automat Natl Key Lab Sci & Tech Multispectral Informat Pr Wuhan 430074 Hubei Peoples R China Three Gorges Univ Coll Comp & Informat Technol Yichang 443002 Hubei Peoples R China

ISBN: (数字)9781510617247

ISBN: (纸本)9781510617247;9781510617230

JPEG-LS lossless compression algorithm is used in many specialized applications that emphasize on the attainment of high fidelity for its lower complexity and better compression ratios than the lossless JPEG standard. But it cannot prevent error diffusion because of the context dependence of the algorithm, and have low compression rate when compared to lossy compression. In this paper, we firstly divide the image into two parts: ROI regions and non-ROI regions. Then we adopt a block-based image compression technique to decrease the range of error diffusion. We provide JPEG-LS lossless compression for the image blocks which include the whole or part region of interest (ROI) and JPEG-LS near lossless compression for the image blocks which are included in the non-ROI (unimportant) regions. Finally, a set of experiments are designed to assess the effectiveness of the proposed compression method.

关键词： image compression Lossy compression Lossless compression Region of interest

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A Fast Method for Single image Haze Removal Based on Multiscale Dark Channel Prior 10

A Fast Method for Single Image Haze Removal Based on Multisc...

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Parallel processing of images and Optimization Techniques;and Medical Imaging

作者： Hong, Hanyu Liu, Zhao Shi, Yu Hua, Xia Wuhan Inst Technol Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

ISBN: (数字)9781510617247

ISBN: (纸本)9781510617247;9781510617230

Aiming at the problem that the computational process in the method for image haze removal based on the dark channel prior is too complicated and too time-consuming, we propose a fast method for single image haze removal based on multiscale dark channel prior. In order to solve the problem that it takes too much time on a high resolution image, we choose to optimize the image haze removal based on dark channel prior algorithm by the method of multiple scales. We deal with rough resolution images and use fast minimum filtering and fast guided filtering to speed up the haze removal algorithm. Therefore, the speed of calculation is accelerated while maintaining the good image effect after haze removal.

关键词： Multiscale haze removal guided filter dark channel fast method

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An improved feature extraction algorithm based on KAZE for multi-spectral image 10

An improved feature extraction algorithm based on KAZE for m...

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Automatic Target recognition and Navigation

作者： Yang, Jianping Li, Jun Guilin Univ Elect Technol Sch Elect Engn & Automat Guilin 541004 Peoples R China Guilin Univ Elect Technol Guangxi Key Lab Optoelect Informat Proc Guilin 541004 Peoples R China

ISBN: (数字)9781510617209

ISBN: (纸本)9781510617209;9781510617193

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

关键词： multi-spectral image KAZE nonlinear scale adjusted-cosine vector

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image quality evaluation of full reference algorithm 10

Image quality evaluation of full reference algorithm

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： He, Nannan Xie, Kai Li, Tong Ye, Yushan Beijing Inst Graph Commun Beijing 102600 Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

image quality evaluation is a classic research topic, the goal is to design the algorithm, given the subjective feelings consistent with the evaluation value. This paper mainly introduces several typical reference methods of Mean Squared Error(MSE), Peak Signal to Noise Rate(PSNR), Structural Similarity image Metric(SSIM) and feature similarity(FSIM) of objective evaluation methods. The different evaluation methods are tested by Matlab, and the advantages and disadvantages of these methods are obtained by analyzing and comparing *** and PSNR are simple, but they are not considered to introduce HVS characteristics into image quality evaluation. The evaluation result is not ideal. SSIM has a good correlation and simple calculation,because it is considered to the human visual effect into image quality evaluation,However the SSIM method is based on a hypothesis,The evaluation result is limited. The FSIM method can be used for test of gray image and color image test, and the result is better. Experimental results show that the new image quality evaluation algorithm based on FSIM is more accurate.

关键词： objective evaluation method full reference evaluation Matlab MSE PSNR SSIM FSIM

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Automatic Road Extraction from High Resolution Remote Sensing image by Means of Topological Derivative and Mathematical Morphology 10

Automatic Road Extraction from High Resolution Remote Sensin...

引用

10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： Zhou, Hongyu Song, Xu Liu, Guoying Anyang Normal Univ Sch Comp & Informat Engn Anyang 455000 Henan Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

Automatic road extraction from High Resolution Remote Sensing image is a challenging problem. In this paper we present a new approach for road automatically extraction which is based on topological derivative and mathematical morphology. This approach for road extraction can be divided into three main steps: using topological derivative for image segmentation, using mathematical morphology for road network identification and filtering. The experimental results show that this approach can effectively extract roads from high-resolution remote sensing image.

关键词： Topological Derivative Road Extraction Mathematical Morphology

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A localization algorithm of adaptively determining the ROI of the reference circle in image 10

A localization algorithm of adaptively determining the ROI o...

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： Xu, Zeen Zhang, Jun Zhang, Daimeng Liu, Xiaomao Tian, Jinwen HUST Sch Automat State Key Lab Multispectral Informat Proc Technol Wuhan 430074 Hubei Peoples R China Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA HUST Sch Math & Stat Wuhan 430074 Hubei Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

Aiming at solving the problem of accurately positioning the detection probes underwater, this paper proposed a method based on computer vision which can effectively solve this problem. The theory of this method is that: First, because the shape information of the heat tube is similar to a circle in the image, we can find a circle which physical location is well known in the image, we set this circle as the reference circle. Second, we calculate the pixel offset between the reference circle and the probes in the picture, and adjust the steering gear through the offset. As a result, we can accurately measure the physical distance between the probes and the under test heat tubes, then we can know the precise location of the probes underwater. However, how to choose reference circle in image is a difficult problem. In this paper, we propose an algorithm that can adaptively confirm the area of reference circle. In this area, there will be only one circle, and the circle is the reference circle. The test results show that the accuracy of the algorithm of extracting the reference circle in the whole picture without using ROI (region of interest) of the reference circle is only 58.76% and the proposed algorithm is 95.88%. The experimental results indicate that the proposed algorithm can effectively improve the efficiency of the tubes detection.

关键词： heat tubes detection probes reference circle adaptive ROI image positioning

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A Novel Attack Method About Double-random-phase-encoding-based image Hiding Method 10

A Novel Attack Method About Double-random-phase-encoding-bas...

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： Xu, Hongsheng Xiao, Zhijun Zhu, Xianchen Hubei Univ Automot Technol Sch Elect & Informat Engn Shiyan 442001 Hubei Peoples R China Dongfeng Commercial Vehicle Co Dept Proc & IT Wuhan Hubei Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

By using optical image processing techniques, a novel text encryption and hiding method applied by double-random phase-encoding technique is proposed in the paper. The first step is that the secret message is transformed into a 2 dimension array. The higher bits of the elements in the array are used to fill with the bit stream of the secret text, while the lower bits are stored specific values. Then, the transformed array is encoded by double random phase encoding technique. Last, the encoded array is embedded on a public host image to obtain the image embedded with hidden text. The performance of the proposed technique is tested via analytical modeling and test data stream. Experimental results show that the secret text can be recovered either accurately or almost accurately, while maintaining the quality of the host image embedded with hidden data by properly selecting the method of transforming the secret text into an array and the superimposition coefficient.

关键词： double-random phase-encoding text encryption text hiding image

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An image-based Automatic recognition Method for the Flowering Stage of Maize 10

An Image-based Automatic Recognition Method for the Flowerin...

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10th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： Yu, Zhenghong Zhou, Huabing Li, Cuina Guangdong Polytech Sci & Technol Zhuhai Key Lab Adv Equipment Mfg & Mat Proc Techn Zhuhai 519090 Peoples R China Wuhan Inst Technol Hubei Key Lab Intelligent Robot Wuhan 430073 Hubei Peoples R China Chinese Acad Sci Inst Atmospher Phys Beijing 100029 Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

In this paper, we proposed an image-based approach for automatic recognizing the flowering stage of maize A modified HOG/SVM detection framework is first adopted to detect the ears of maize Then, we use low-rank matrix recovery technology to precisely extract the ears at pixel level. At last, a new feature called color gradient histogram, as an indicator, is proposed to determine the flowering stage. Comparing experiment has been carried out to testify the validity of our method and the results indicate that our method can meet the demand for practical observation.

关键词： Automatic recognition Maize Flowering Stage Low-rank Recovery Color Gradient Histogram

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Robust object tacking based on self-adaptive search area 10

Robust object tacking based on self-adaptive search area

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10th international symposium on multispectral image processing and pattern recognition, MIPPR 2017

作者： Dong, Taihang Zhong, Sheng Science and Technology on Multispectral Information Processing Laboratory China School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

ISBN: (数字)9781510617209

ISBN: (纸本)9781510617193

Discriminative correlation filter (DCF) based trackers have recently achieved excellent performance with great computational efficiency. However, DCF based trackers suffer boundary effects, which result in the unstable performance in challenging situations exhibiting fast motion. In this paper, we propose a novel method to mitigate this side-effect in DCF based trackers. We change the search area according to the prediction of target motion. When the object moves fast, broad search area could alleviate boundary effects and reserve the probability of locating object. When the object moves slowly, narrow search area could prevent effect of useless background information and improve computational efficiency to attain real-time performance. This strategy can impressively soothe boundary effects in situations exhibiting fast motion and motion blur, and it can be used in almost all DCF based trackers. The experiments on OTB benchmark show that the proposed framework improves the performance compared with the baseline trackers. © 2018 SPIE.

关键词： Computational efficiency

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