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IET International Radar Conference 2013

作者： Hui, Zhang Jun, Hong University of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Beijing Institute of Electronics China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Technology Beijing China Science and Technology on Microwave Imaging Laboratory Beijing China

ISBN: (纸本)9781849196031

Along-Track Interferometric Synthetic Aperture Radar (ATISAR) has the potential of measuring the radial velocity of the slowly moving target. The accuracy of the radial velocity is mainly determined by the accuracy of the interferometric parameters. Sensitivity equations are good ways of analysing the impacts of system parameters for interferometric SAR. Former sensitivity analysis for ATI-SAR has been mainly focused on the case of no squint angle. In this paper, we explain the necessity of analysing the sensitivity equations in the presence of squint angle. Then the expression of the radial velocity in the presence of squint is derived and the sensitivity equations are obtained. Finally, the sensitivity of some interferometric parameters and the impact of squint angles are analysed and simulated for a particular accuracy requirement.

关键词： Sensitivity analysis

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Nonparametric statistics inspired similarity measure for accuracy in collaborative filtering

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Journal of Computational information systems 2013年第20期9卷 8397-8406页

作者： Liu, Shichen Xiong, Yan Liu, Qingwen Qi, Xiang Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

Similarity computation is especially significant in collaborative filtering algorithms. In the existed literatures or large recommender systems, researchers generally use cosine similarity or Pearson correlation coefficient to compute the similarities. However, on one hand, both two measures are more applicable in linear space while the ratings cannot linearly reflect users' interest intensity. On the other hand, different systems have different rating restricts, so it's unreasonable to treat varied systems with the same computation method. In this work, inspired by nonparametric statistics, a sound memory-based method with a novel similarity measure is proposed to eliminate the affection of rating distributions and system diversities on similarity computation. Experiments based on Jester are set to evaluate the performance of the approach. And the highly competitive results show that our approach is able to significantly improve the recommendation quality. © 2013 Binary information Press.

关键词： Collaborative filtering

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Self-adaptive optical image registration based on optimized analysis of feature points

Self-adaptive optical image registration based on optimized ...

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第二届高分辨率对地观测学术年会

作者： Shi Yue Zhang Daobing Institute of Electronic Chinese Academy of SciencesBeijing 100190China Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy o

Image registration is an important preprocessing step for image processing such as change detection,image mosaicking in remote sensing,however a crucial problem involved feature-based image registration is how to reliably establish correspondent features between sensed image and reference *** paper presents an automatic self-adaptive image registration method based on analytic energy of control points to improve the traditional ***,an multi-scale segment method based on digital curvelet transform is used to evaluate the quality difference of image pairs,and then self-adaptive parameters of SIFT feature-matching algorithm based on multi-scale grey relation of image quality is proposed to increase the feature points and correspondences;At last,to make sure the accuracy of geometrical transform parameters,a method of correspondences selection based on the distribution and matching energy of control points is *** results demonstrate that the proposed method works well in increasing control points and the correspondences of low quality remote sensing images.

关键词： Image Registration Scale Invariant Feature Transform (SIFT) Self-adaptive keypoint refinement

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MACHINE LEARNING-BASED MULTI-CHANNEL EVALUATION POOLING STRATEGY FOR IMAGE QUALITY ASSESSMENT

MACHINE LEARNING-BASED MULTI-CHANNEL EVALUATION POOLING STRA...

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IEEE International Conference on Image processing

作者： Anzhou Hu Rong Zhang Dong Yin Wenlong Hu Department of Electronic Engineering and Information Science University of Science and Technology of China Key Laboratory of Geospatial Information Processing and Application System Technology Chinese Academy of Sciences

ISBN: (纸本)9781479923427

Multi-channel peculiarity is one of the most widely accepted human visual system (HVS) models for perceptual image quality assessment (IQA). Otherwise than extensive studies of channel decomposition and intra-channel distortion measure, relatively scant research effort has been devoted to develop efficient multichannel evaluation pooling strategies. In this paper, we review and address the limitations of the conventional pooling models based on HVS sensitivities-weighted average. Instead, we explore the utilization of machine learning for this pooling problem, since machine learning can establish an optimal and generalized mapping that models the highly complex relationship between the multi-channel distortion evaluations and the perceived image quality. Experiments based on available subjective IQA databases demonstrate the rationality, reliability and robustness of our proposed scheme.

关键词： Image quality assessment (IQA) Multi-channel model Evaluation pooling Machine learning

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Rapid face image retrieval with pose-based local features and multi-reference re-ranking

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Journal of Computational information systems 2013年第1期9卷 223-230页

作者： Zhen, Haiyang Zeng, Lingzi Zhang, Rong Yin, Dong Department of Electronic Eng. and Information Science University of Science and Technology of China Hefei 230027 China Key Laboratory of Geospatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing 100190 China

The performance of state-of-art image retrieval systems using Bag-of-Words representation and textual retrieval methods degrades quickly when applied to face images because their local features can not suffer variations of illumination, pose and expression of human face. Moreover, most discriminative facial features are typically high-dimensional and global, and not suitable for rapid retrieval. Motivated by the observation that local features and global features are complementary, we propose a rapid face image retrieval approach using both local and global features in this paper. To ensure the high speed of retrieval, an inverted index is built by quantizing pose-based local features specially designed for face images on component level. Candidate images with low precision and high recall can be obtained using inverted index of visual words in the retrieval stage. Global facial features and multi-reference method are used to obtain a final retrieval list with high precision. Experiments on a 160k face dataset downloaded from the internet show our approach can achieve a high precision and a high speed. © 2013 Binary information Press.

关键词： Indexing (of information)

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REMOTE SENSING IMAGE COMPRESSION BASED ON DOUBLE-SPARSITY DICTIONARY LEARNING AND UNIVERSAL TRELLIS CODED QUANTIZATION

REMOTE SENSING IMAGE COMPRESSION BASED ON DOUBLE-SPARSITY DI...

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IEEE International Conference on Image processing

作者： Xin Zhan Rong Zhang Dong Yin Anzhou Hu Wenlong Hu Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei 230027 China Key Laboratory of Geospatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479923427

In this paper, we propose a novel remote sensing image compression method based on double-sparsity dictionary learning and universal trellis coded quantization (UTCQ). Recent years have seen a growing interest in the study of natural image compression based on sparse representation and dictionary learning. We show that using the double-sparsity model to learn a dictionary gives much better compression results for remote sensing images, the texture of which is much richer than that of natural images. We also show that the compression performance is improved significantly when advanced quantization and entropy coding strategies are used for encoding the sparse representation coefficients. The proposed method outperforms the existing dictionary-based image coding algorithms. Additionally, our method results in better rate-distortion performance and structural similarity results than CCSDS and JPEG2000 standard.

关键词： Dictionary learning image compression remote sensing universal trellis coded quantization

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IMPROVED CALIBRATION METHOD FOR AIRBORNE ATI-SAR BASELINE

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Journal of Electronics(China) 2012年第5期29卷 368-374页

作者： Wang Xin Hong Jun Institute of Electronics Chinese Academy of Sciences Key Laboratory of Geo-spatial Information Processing and Application System Technology Graduate University of Chinese Academy of Sciences

Airborne Along-Track Interferometric Synthetic Aperture Radar (ATI-SAR) baseline error is a main error resource affecting the precision of velocity measurement of moving objects and therefore should be calibrated externally. The Jet Propulsion laboratory (JPL) has proposed a calibration scheme for tasks of PacRim98 and PacRim2000 based on several static objects on the ground. In this paper, the influence of phase center uncertainty on baseline determination by using PacRim method proposed by JPL is analyzed. According to the analysis, the phase center uncertainty can cause a constant part of error to the result of baseline calibration. In order to deal with this problem, an improved calibration method on the basis of sensitivity equations and some ground moving targets, whose velocities are already known, is proposed in this paper. The simulation results show that our proposed calibration method has improved the accuracy of baseline calibration and has obviously prohibited the effect of antennas' phase center uncertainty.

关键词： Airborne Along-Track Interferometric Synthetic Aperture Radar (ATI-SAR) Baseline error Baseline calibration Sensitivity equation

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MULTIPLE KERNEL RELEVANCE VECTOR MACHINE FOR geospatial OBJECTS DETECTION IN HIGH-RESOLUTION REMOTE SENSING IMAGES

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Journal of Electronics(China) 2012年第5期29卷 353-360页

作者： Li Xiangjuan Sun Xian Wang Hongqi Li Yu Sun Hao Institute of Electronics Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Graduate University Chinese Academy of Sciences

geospatial objects detection within complex environment is a challenging problem in remote sensing area. In this paper, we derive an extension of the Relevance Vector Machine (RVM) technique to multiple kernel version. The proposed method learns an optimal kernel combination and the associated classifier simultaneously. Two feature types are extracted from images, forming basis kernels. Then these basis kernels are weighted combined and resulted the composite kernel exploits interesting points and appearance information of objects simultaneously. Weights and the detection model are finally learnt by a new algorithm. Experimental results show that the proposed method improve detection accuracy to above 88%, yields good interpretation for the selected subset of features and appears sparser than traditional single-kernel RVMs.

关键词： Object detection Feature extraction Relevance Vector Machine (RVM) Support Vector Machine (SVM) Sliding-window

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Investigations of the dynamics of road pavement reflectance

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Chinese Optics Letters 2012年第4期10卷 58-62页

作者：姜亢于凯赵永超 Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of ElectronicsChinese Academy of Sciences Graduate University of Chinese Academy of Sciences

Road pavement reflectance is usually assumed to be invariant in short periods of time in some quantitative remote sensing *** examine its variability,reflectance sequences of concrete and asphalt pavement are measured in field for half a day in visible and near-infarecd（VNIR）spectral range using dual-beam *** much as 20.7%and 3.52%of relative changes are found in asphalt and concrete reflectance data at 550 nm,and all VNIR bands demonstrate similar variations found to correlate with both illumination geometry and the relative portion of diffuse *** this letter,this effect is interpreted from a mathematic *** studies are needed to model the dynamics of reflectance physically.

关键词： Dynamics Remote sensing Roads and streets

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A New Approach to Airborne High Resolution SAR Motion Compensation for Large Trajectory Deviations

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电子学报(英文版) 2012年第4期21卷 764-769页

作者： MENG Dadi HU Donghui DING Chibiao Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing 100190 China Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

The Two-step algorithm (TSA) is widely used for trajectory deviation compensation of airborne Synthetic aperture radar (SAR), by which most of the mo- tion errors are compensated before Range curve migration compensation (RCMC) and the residual after the RCMC. We found that the RCMC in the presence of the residual motion errors results in additional range shift errors hard to be compensated for. Based on theoretical investiga- tions, this shortage of TSA is reported and a new compen- sation scheme which greatly alleviates the RCMC induced errors is proposed. Besides, range resampling considering the residual motion errors is very convinent, which, how- ever, is boresome in TSA. The new method is effective to compensate the high resolution SAR systems for large tra- jectory deviations, which is hard to be achieved by TSA because of the uncompensated errors. Results on the sim- ulated data are provided to demonstrate the effectiveness of the new method.

关键词：机载合成孔径雷达高分辨率SAR 运动补偿弹道偏差运动误差 TSA 偏差补偿误差范围 Synthetic aperture radar （SAR）, Motion compensation, Space variant.

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