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检索条件"任意字段=10th International Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2017"

共 99 条记录，以下是11-20 订阅

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Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images 10

Gaussian mixture models-based ship target recognition algori...

引用

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

作者： Yao, Shoukui Qin, Xiaojuan Huazhong Univ Sci & Technol Sch Automat Natl Key Lab Sci & Technol Multispectral Informat Wuhan Hubei Peoples R China

ISBN: (数字)9781510617209

ISBN: (纸本)9781510617209;9781510617193

Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. the issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

关键词： Ship target recognition Gaussian mixture model invariant moment remote sensing infrared image

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A Method of Distributed Avionics Data processing Based on SVM Classifier 10

A Method of Distributed Avionics Data Processing Based on SV...

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： Guo Hangyu Wang Jinyan Kang Minyang Xu Guojing Sci & Technol Avion Integrat Lab Shanghai 200233 Peoples R China China Natl Aeronaut Radio Elect Res Inst Shanghai 200233 Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

Under the environment of system combat, in order to solve the problem on management and analysis of the massive heterogeneous data on multi-platform avionics system, this paper proposes a management solution which called avionics "resource cloud" based on big data technology, and designs an aided decision classifier based on SVM algorithm. We design an experiment with STK simulation, the result shows that this method has a high accuracy and a broad application prospect.

关键词： distributed avionics big data data processing assistant decision-making

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Infrared and visible images fusion based on visual saliency map and NSCT 10

Infrared and visible images fusion based on visual saliency ...

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10th international symposium on multispectral image processing and pattern recognition (mippr) - multispectral image Acquisition, processing, and Analysis (mippr)

作者： Chen, Yanfei Cao, Min Li, Wenxiang Wuhan Inst Technol Sch Elect & Informat Engn Hubei Key Lab Intelligent Robot Wuhan 430073 Hubei Peoples R China

ISBN: (数字)9781510617186

ISBN: (纸本)9781510617186;9781510617179

A fusion algorithm of infrared and visible images based on visual saliency map (VSM) and nonsubsampled contourlet transform (NSCT) was proposed. Usually, the visual salient region of infrared image is directed towards the targets which interpret the most important information in the image. For the given registered infrared and visible images, firstly, the frequency-tuned (FT) saliency detection algorithm is used to calculate the visual saliency map of infrared and visible images. then the size of each salient region is obtained by maximizing entropy. In order to capture the details of the infrared and visible images, the low and high frequency fusion coefficients of nonsubsampled contourlet transform (NSCT) are selected based on region saliency, region energy (RE) and region sharpness (RS). Four different data sets from TNO, Human Factors are employed, and experimental results indicate that the proposed method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.

关键词： image fusion visual saliency map (VSM) nonsubsampled contourlet transform (NSCT) infrared image

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Mapping soil total nitrogen of cultivated land at county scale by using hyperspectral image 10

Mapping soil total nitrogen of cultivated land at county sca...

引用

10th international symposium on multispectral image processing and pattern recognition (mippr) - multispectral image Acquisition, processing, and Analysis (mippr)

作者： Gu, Xiaohe Zhang, Li Yan Shu, Meiyan Yang, Guijun Beijing Res Ctr Informat Technol Agr Beijing 100097 Peoples R China

ISBN: (数字)9781510617186

ISBN: (纸本)9781510617186;9781510617179

Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agriculture. the study aimed to develop a universal method to map total nitrogen content in soil of cultivated land by HSI image at county scale. Several mathematical transformations were used to improve the expression ability of HSI image. the correlations between soil TNC and the reflectivity and its mathematical transformations were analyzed. then the susceptible bands and its transformations were screened to develop the optimizing model of map soil TNC in the Anping County based on the method of multiple linear regression. Results showed that the bands of 14th, 16th, 19th, 37th and 60th with different mathematical transformations were screened as susceptible bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. the determination coefficient of the first order differential of logarithmic transformation was biggest (0.505), while the RMSE was lowest. the study confirmed the first order differential of logarithm transformation as the optimal inversion model for soil TNC, which was used to map soil TNC of cultivated land in the study area.

关键词： HJ-HSI soil total nitrogen multiple linear regressions hyperspectral image cultivated land

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Segmentation of oil spills in SAR images by using discriminant cuts 10

Segmentation of oil spills in SAR images by using discrimina...

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

作者： Ding, Xianwen Zou, Xiaolin Shanghai Ocean Univ Shanghai Coll Marine Sci Shanghai 201306 Peoples R China Zhaoqing Univ Sch Math & Stat Zhaoqing 526061 Peoples R China

ISBN: (数字)9781510617209

ISBN: (纸本)9781510617209;9781510617193

the discriminant cut is used to segment the oil spills in synthetic aperture radar (SAR) images. the proposed approach is a region-based one, which is able to capture and utilize spatial information in SAR images. the real SAR images, i.e. ALOS-1 PALSAR and Sentinel-1 SAR images were collected and used to validate the accuracy of the proposed approach for oil spill segmentation in SAR images. the accuracy of the proposed approach is higher than that of the fuzzy C-means classification method.

关键词： SAR oil spill image segmentation discriminant cuts

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Different Focus image Fusion Based on Multi-level Scaling 10

Different Focus Image Fusion Based on Multi-level Scaling

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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： Qian, Ruiyan Lu, Zhenkun Guangxi Univ Nationalities Coll Informat Sci & Engn Nanning 530006 Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

Based on the idea of iteration, a simple and effective method for multi-focus image fusion is proposed. Firstly, two images are processed by Gaussian convolution, and the blurred images are obtained. then, the area decision of image blocks are obtained through the original image subtracting the blurred images at different blocks and different levels. According to the principle of consistency, the subjection of image blocks is obtained by the area decision of image blocks. the area partition map is obtained by the subjection map at different levels. Finally, the fused image is obtained through the method of coefficient weighting. the experimental results show that the image quality obtained by the proposed method is superior to the traditional fusion method.

关键词： image fusion Block iteration multi-focus

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Feature Extraction based on Extended Multi-Attribute Profiles and Sparse Autoencoder for Remote Sensing image Classification 10

Feature Extraction based on Extended Multi-Attribute Profile...

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10th international symposium on multispectral image processing and pattern recognition (mippr) - multispectral image Acquisition, processing, and Analysis (mippr)

作者： Teffahi, Hanane Yao, Hongxun Belabid, Nasreddine Chaib, Souleyman Harbin Inst Technol Sch Comp Sci & Technol Harbin Heilongjiang Peoples R China Algerian Space Agcy Algiers Algeria Beijing Univ Aeronaut & Astronaut Space Technol Applicat Sch Instrument Sci & Technol Beijing Peoples R China

ISBN: (数字)9781510617186

ISBN: (纸本)9781510617186;9781510617179

the satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become a challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. this paper proposes a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. the proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral images "KSC" and "Pavia university" datasets and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers, and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

关键词： Hyperspectral image multispectral image spatial feature extraction dimensionality reduction image classification deep learning (DL) sparse autoencoder (SAE) extend multi-attribute profiles (EMAP) support vector machine (SVM)

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Complex Background Suppression Using Global-local Registration Strategy for the Detection of Small-Moving Target On Moving Platform 10

Complex Background Suppression Using Global-local Registrati...

引用

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

作者： Zou, Tianhao Zuo, Zhengrong Huazhong Univ Sci & Technol Natl Key Lab Sci & Technol Multispectral Informat Wuhan 430074 Hubei Peoples R China

ISBN: (数字)9781510617209

ISBN: (纸本)9781510617209;9781510617193

Target detection is a very important and basic problem of computer vision and image processing. the most often case we meet in real world is a detection task for a moving-small target on moving platform. the commonly used methods, such as Registration-based suppression, can hardly achieve a desired result. To crack this hard nut, we introduce a Global-local registration based suppression method. Differ from the traditional ones, the proposed Global-local Registration Strategy consider both the global consistency and the local diversity of the background, obtain a better performance than normal background suppression methods. In this paper, we first discussed the features about the small-moving target detection on unstable platform. then we introduced a new strategy and conducted an experiment to confirm its noisy stability. In the end, we confirmed the background suppression method based on global-local registration strategy has a better perform in moving target detection on moving platform.

关键词： image registration global optimize local rematch

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Gas leak detection in Infrared video with Background Modeling 10

Gas leak detection in Infrared video with Background Modelin...

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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： Zeng, Xiaoxia Huang, Likun Wuhan Inst Technol Sch Elect & Informat Engn Wuhan 430074 Hubei Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

Background modeling plays an important role in the task of gas detection based on infrared video. VIBE algorithm is a widely used background modeling algorithm in recent years. However, the processing speed of the VIBE algorithm sometimes cannot meet the requirements of some real time detection applications. therefore, based on the traditional VIBE algorithm([1][2]), we propose a fast prospect model and optimize the results by combining the connected domain algorithm and the nine-spaces algorithm in the following processing steps. Experiments show the effectiveness of the proposed method.

关键词： gray-background model fast-foreground model VIBE algorithm connected domain denoising morphology processing gas detection background modeling the neighborhood propagation method

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Aircraft Target Detection Algorithm Based on High Resolution Spaceborne SAR imagery 10

Aircraft Target Detection Algorithm Based on High Resolution...

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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： Zhang, Hui Hao, Mengxi Zhang, Cong Su, Xiaojing Beijing Aerosp Automat Control Inst Natl Key Lab Sci & Technol Aerosp Intelligent Con Beijing 100854 Peoples R China

ISBN: (数字)9781510617261

ISBN: (纸本)9781510617261;9781510617254

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. the algorithm combines Gamma mixture model and MRF. the algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

关键词： SAR image airport classification aircraft target detection

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