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2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

作者： Ma, Jianglin Zhang, Zhouwei Wang, Chengyi Chen, Zhong Remote Sensing Image Processing Laboratory Institute of Remote Sensing Applications CAS Beijing China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424449941

A classifier-based method to select and fuse grey level co-occurrence matrix (GLCM), Gaussian Markov random field (GMRF) and discrete wavelet transform (DWT) features to improve texture discrimination is presented. Feature selection via wrapper approaches is applied to find the optimal combination of texture features. The fused features have obtained higher discrimination accuracy compared with individual features. The curse of dimensionality is shown to affect discrimination accuracy, and feature selection and reduction helps obtain higher accuracy. Overall our proposed classifier-based method obtains the highest discrimination accuracy compared to other feature reduction methods such as principal component analysis (PCA) and linear discriminant analysis (LDA). Meanwhile GLCM features are found to produce higher discrimination accuracy than GMRF and DWT, and LDA is demonstrated to obtain higher discrimination accuracy than PCA. ©2009 IEEE.

关键词： Discrete wavelet transforms

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MULTISPECTRAL REMOTE SENSING IMAGE CLASSIFICATION WITH MULTIPLE FEATURES

MULTISPECTRAL REMOTE SENSING IMAGE CLASSIFICATION WITH MULTI...

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2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： QIAN YIN PING GUO Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 Chin Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 Chin

In this paper, we propose to combine the spectral and texture features to compose the multi-feature vectors for the classification of multispectral remote sensing *** usually is difficult to obtain the higher classification accuracy if only considers one kind feature, especially for the case of different geographical objects have the same spectrum or texture specialty for a multispectral remote sensing *** spectral feature and the texture feature are composed together to form a new feature vector, which can represent the most effective features of the given remote sensing *** this way we can overcome shortcomings of only using the single feature and raise the classification *** system classification performance with composed feature vector is investigated by *** analysis of results we can learn how to combine the multi-feature vector can obtain a higher classification rate, and experiments proved that the proposed method is feasible and useful in multispectral remote sensing image classification study.

关键词： Spectrum feature Texture feature Multispectral remote sensing image Feature combination Classification.

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Object tracking within the framework of concept drift

Object tracking within the framework of concept drift

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11th Asian Conference on Computer Vision, ACCV 2012

作者： Chen, Li Zhou, Yue Yang, Jie Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642374302

It is well known that the backgrounds or the targets always change in real scenes, which weakens the effectiveness of classical tracking algorithms because of frequent model mismatches. In this paper, an object tracking algorithm within the framework of concept drift is proposed to solve this problem. We detect the driftpoints using a simple message-passing algorithm based on Bayesian Approach. The analyzed probability distribution lays the foundation for the self-adaption of our new model. Our tracking algorithm within the framework of concept drift improves the tracking robustness and accuracy which is illustrated by the two experiments on two real-world changing scenes. © 2013 Springer-Verlag.

关键词： Probability distributions

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Research on large-scale scene infrared simulation based on image classification

Research on large-scale scene infrared simulation based on i...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zou, Lamei Zhang, Tianxu Lv, Wei Ao, Guoqing Institute for Pattern Recognition and Artificial Intelligence Natl. Key Laboratory of Science and Technology on Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424494040

Vega has been widely used in Virtual Reality (VR) field. Vega infrared (IR) module can implement IR simulation, but Vega IR imaging simulation's general approach does not apply to large-scale scene's infrared simulation problem. This article deeps into large-scale scene IR image simulation through Vega infrared module based on visible image, the scene's corresponding Digital Elevation Model (DEM) data and targets' 3D model. A real time large-scale IR simulation system is successfully designed and realized in this paper. At the aspect of image classification, a coarse to fine k-means clustering method based on the consistency of image color is proposed. The proposed automatic texture material mapping method based on the development of Vega TMM tool provides a fast and convenient way for large-scale scene's IR simulation based on Vega IR module. And finally, results of the large-scale scene infrared simulation show the effectiveness of this method. ©2011 IEEE.

关键词： Image classification

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Radio frequency interference mitigation using pseudoinverse learning autoencoders

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Research in Astronomy and Astrophysics 2020年第8期20卷 121-128页

作者： Hong-Feng Wang Mao Yuan Qian Yin Ping Guo Wei-Wei Zhu Di Li Si-Bo Feng Image Processing and Pattern Recognition Laboratory School of Artificial IntelligenceBeijing Normal UniversityBeijing 100875China CAS Key Laboratory of FAST National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China School of Information Management Dezhou UniversityDezhou 253023China Image Processing and Pattern Recognition Laboratory School of System ScienceBeijing Normal UniversityBeijing 100875China Institute for Astronomical Science Dezhou UniversityDezhou 253023China University of Chinese Academy of Sciences Beijing 100049China Hanvon Technology Co. LtdBeijing 100193China NAOC-UKZN Computational Astrophysics Centre University of KwaZulu-NatalDurban 4000South Africa

Radio frequency interference(RFI)is an important challenge in radio *** comes from various sources and increasingly impacts astronomical observation as telescopes become more *** this study,we propose a fast and effective method for removing RFI in pulsar *** use pseudo-inverse learning to train a single hidden layer auto-encoder(AE).We demonstrate that the AE can quickly learn the RFI signatures and then remove them from fast-sampled spectra,leaving real pulsar *** method has the advantage over traditional threshold-based filter method in that it does not completely remove contaminated channels,which could also contain useful astronomical information.

关键词： pulsars:general methods:numerical methods:data analysis

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An FPGA-based histogram equalization implementation

An FPGA-based histogram equalization implementation

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MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Li, Yang Zhong, Sheng Wang, Bo Yan, Luxin Liu, Tao Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China National Key Laboratory of Multi-spectral Information Processing Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Image histogram equalization technology is always a very important basic processing technology in image process field. In infrared image processing system, low contrast and shortage of gray levels often make it very difficult to observe and recognize targets. In this situation, Real-time image histogram equalization technology is often used to enhance infrared image contrast, improve infrared image quality and ameliorate image processing system performance. In embedded system, when real-time image histogram equalization is required, it is very difficult for the typical design methods by using general purpose DSP or MCU to meet the real-time requirement. It is a very good choice to choose FPGA hardware logic to implement image histogram equalization. Here in this paper, we introduce an FPGA based image histogram equalization implementation in detail which can meet real-time requirement very well. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image enhancement

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Restoration of rotational motion blurred image based on chebyshev polynomial interpolations

Restoration of rotational motion blurred image based on cheb...

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MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Zhang, Tianxu Hong, Hanyu Yan, Luxin Zhang, Xiuhua Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

The restoration of rotational motion blurred image involves a lot of interpolations operators in rectangular-to-polar transformation and its inversion of polar-to-rectangular. The technique of interpolation determines the quality of restoration and computational complexity. In this paper, we incorporate orthogonal chebyshev polynomials interpolations into the processing of restoration of rotational motion blurred image, in which the space-variant blurs are decomposed into a series of space-invariant blurs along the blurring paths, and the blurred gray-values of the discrete pixels of the blurring paths are calculated by using of orthogonal chebyshev polynomials' interpolations and the space-variant blurs can be removed along the blurring paths in the polar system. At same way, we use orthogonal chebyshev polynomials' interpolations to perform polar-to-rectangular transformation to put the restored image back to its original rectangular format. In order to overcome the interference of noise, an optimization restoration algorithm based on regularizations is presented, in which non-negative and edge-preserving smoothing are incorporated into the process of restoration. A series of experiments have been performed to test the proposed interpolation method, which show that the proposed interpolations are effective to preserve edges. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Chebyshev polynomials

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A framework of passive millimeter-wave imaging simulation for typical ground scenes

A framework of passive millimeter-wave imaging simulation fo...

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MIPPR 2009 - Multispectral Image Acquisition and processing: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Yan, Luxin Ge, Rui Zhong, Sheng Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China National Key Laboratory of Multi-spectral Information Processing Technology Wuhan 430074 China

ISBN: (纸本)9780819478054

Passive millimeter-wave (PMMW) imaging offers advantages over visible and IR imaging in having better all weather performance. However the PMMW imaging sensors are state-of-the-art to date, sometimes it is required to predict and evaluate the performance of a PMMW sensor under a variety of weather, terrain and sensor operational conditions. The PMMW scene simulation is an efficient way. This paper proposes a framework of the PMMW simulation for ground scenes. Commercial scene modeling software, Multigen and Vega, are used to generate the multi-viewpoint and multi-scale description for natural ground scenes with visible images. The background and objects in the scene are classified based on perceptive color clusters and mapped with different materials. Further, the radiometric temperature images of the scene are calculated according to millimeter wave phenomenology: atmospheric propagation and emission including sky temperature, weather conditions, and physical temperature. Finally, the simulated output PMMW images are generated by applying the sensor characteristics such as the aperture size, data sample scheme and system noise. Tentative results show the simulation framework can provide reasonable scene's PMMW image with high fidelity. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Infrared imaging

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New method for laser parameter detection

New method for laser parameter detection

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4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment

作者： Hong, Hanyu Zhang, Huimin Wan, Xiang Zhang, Xiuhua Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of science and technology Wuhan 430074 China

ISBN: (纸本)9780819475435

A new method to detect laser parameter is proposed in this paper. The improved Michelson Interferometer is used as experiment system to detect parameter. In the proposed detection method, the interference images in variant atmosphere visibility by regulating the polarizer in the system simulate the transmissibility of laser. Experimental results show that the proposed scheme can simulate laser parameter in true atmosphere environment and has good application value. © 2009 SPIE.

关键词： Michelson interferometers

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ChromTR:chromosome detection in raw metaphase cell images via deformable transformers

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Frontiers of Medicine 2024年第6期18卷 1100-1114页

作者： Chao Xia Jiyue Wang Xin You Yaling Fan Bing Chen Saijuan Chen Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityShanghai200240China Shanghai Institute of Hematology State Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai200025China

Chromosome karyotyping is a critical way to diagnose various hematological malignancies and genetic diseases,of which chromosome detection in raw metaphase cell images is the most critical and challenging *** this work,focusing on the joint optimization of chromosome localization and classification,we propose ChromTR to accurately detect and classify 24 classes of chromosomes in raw metaphase cell *** incorporates semantic feature learning and class distribution learning into a unified DETR-based detection ***,we first propose a Semantic Feature Learning Network(SFLN)for semantic feature extraction and chromosome foreground region segmentation with object-wise ***,we construct a Semantic-Aware Transformer(SAT)with two parallel encoders and a Semantic-Aware decoder to integrate global visual and semantic *** provide a prediction with a precise chromosome number and category distribution,a Category Distribution Reasoning Module(CDRM)is built for foreground-background objects and chromosome class distribution *** evaluate ChromTR on 1404 newly collected R-band metaphase images and the public G-band dataset *** proposed ChromTR outperforms all previous chromosome detection methods with an average precision of 92.56%in R-band chromosome detection,surpassing the baseline method by 3.02%.In a clinical test,ChromTR is also confident in tackling normal and numerically abnormal *** extended to the chromosome enumeration task,ChromTR also demonstrates state-of-the-art performances on R-band and G-band two metaphase image *** these superior performances to other methods,our proposed method has been applied to assist clinical karyotype diagnosis.

关键词： chromosome detection deformable transformer metaphase cell image distribution reasoning

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