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IEEE International Conference on Image processing

作者： Changyue Ma Dong Liu Xiulian Peng Feng Wu CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China Microsoft Research Asia Beijing China

In the state-of-the-art video coding standard-High Efficiency Video Coding (HEVC), context-adaptive binary arithmetic coding (CABAC) is adopted as the entropy coding tool. In CABAC, the binarization processes are manually designed, and the context models are empirically crafted, both of which incur that the probability distribution of the syntax elements may not be estimated accurately, and restrict the coding efficiency. In this paper, we adopt a convolutional neural network-based arithmetic coding (CNNAC) strategy, and conduct studies on the coding of the DC coefficients for HEVC intra coding. Instead of manually designing binarization process and context model, we propose to directly estimate the probability distribution of the value of the DC coefficient using densely connected convolutional networks. The estimated probability together with the real DC coefficient are then input into a multi-level arithmetic codec to fulfill entropy coding. Simulation results show that our proposed CNNAC leads to on average 22.47% bits saving compared with CABAC for the bits of DC coefficients, which corresponds to 1.6% BD-rate reduction than the HEVC anchor.

关键词： Context modeling Probability distribution Entropy coding Codecs Training data Tools

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Convolutional Neural Network-Based Invertible Half-Pixel Interpolation Filter for Video Coding

Convolutional Neural Network-Based Invertible Half-Pixel Int...

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IEEE International Conference on Image processing

作者： Ning Yan Dong Liu Houqiang Li Tong Xu Feng Wu Bin Li CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei China Microsoft Research Asia Beijing China

Fractional-pixel interpolation has been widely used in the modern video coding standards to improve the accuracy of motion compensated prediction. Traditional interpolation filters are designed based on the signal processing theory. However, video signal is non-stationary, making the traditional methods less effective. In this paper, we reveal that the interpolation filter can not only generate the fractional pixels from the integer pixels, but also reconstruct the integer pixels from the fractional ones. This property is called invertibility. Inspired by the invertibility of fractional-pixel interpolation, we propose an end-to-end scheme based on convolutional neural network (CNN) to derive the invertible interpolation filter, termed CNNInvIF. CNNlnvIF does not need the “ground-truth” of fractional pixels for training. Experimental results show that the proposed CNNInvIF can achieve up to 4.6% and on average 2.2% BD-rate reduction than HEVC under the low-delay P configuration.

关键词： Interpolation Video coding Training Image reconstruction Geometry Convolutional neural networks Image coding

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Identity Regularized Sparse Representation for Automatic Target Recognition in Sar Images

Identity Regularized Sparse Representation for Automatic Tar...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Zongxu Pan Lei Liu Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

An identity regularized sparse representation (IRSR) based SAR target recognition method is proposed in this paper. The method aims to find a transformation that can map the data to a transformed space, in which targets from the same class are close with each other, no matter the distance of them in the original space. This identity constraint can be formulated as a ℓ 1 -norm minimization problem. By decoupling the problem into the sparse coding problem and the dictionary learning problem, the solution can be obtained iteratively. The solution is simply the weighted average of the sparse coding of all training data. Experimental results demonstrate that the proposed method is superior to several related methods.

关键词： Synthetic aperture radar Target recognition Linear programming Airplanes Remote sensing Support vector machines Minimization

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Doppler walk rectification based on KWT in passive radar

Doppler walk rectification based on KWT in passive radar

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xin Guan Li-Hua Zhong Dong-Hui Hu Chi-Biao Ding Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509033331

Doppler walk is introduced by high speed motion of targets in passive radar, which decreases the signal-to-noise ratio. In this paper, a Doppler walk rectification method based on keystone-Wigner-Ville transform (KWT) is proposed, and the interference, weights and noise impact are analyzed. No prior information and parameters searching are unnecessary.

关键词： Doppler effect Interference Transforms Frequency modulation Object detection Passive radar Filtering

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Combined analysis of probability of missed detection and positioning accuracy for receiver selection in SFN based passive radar systems

Combined analysis of probability of missed detection and pos...

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International Conference on Signal processing Proceedings (ICSP)

作者： Xiao-bo Li Xin Guan Li-hua Zhong Dong-hui Hu Chi-biao Ding Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479921898

Multistatic passive radar systems provide higher positioning accuracy comparing with the bistatic ones. However, the positioning performance of the multistatic passive radar systems is largely dependent on the geometry. Especially, it is difficult to designate transmitters from the given ones in a single frequency network (SFN) based passive radar system. Therefore the receiver location is of crucial importance. In this paper, the influence of different receiver positions for the probability of missed detection and the target positioning accuracy are analyzed. Then a performance function for selecting the optimal receiver is proposed. Finally, a simulation with three transmitters and one receiver is presented.

关键词： Accuracy Passive radar Receiving antennas Radio transmitters

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Model selection for high resolution InSAR coherence statistics over urban areas and its application in building detection

Model selection for high resolution InSAR coherence statisti...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yue Zhang Xian Sun Wenhui Diao Chenyuan Wang Guangluan Xu Hongqi Wang Institute of Electronic Chinese Academy of Sciences Beijing China Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509033331

The interferometric coherence map is derived from the cross-correlation of two registered synthetic aperture radar (SAR) images. It can give additional information complementary to the intensity image, or act as an independent information source in many applications. Compared to the plenty of work on SAR intensity statistics, there are quite fewer researches on the statistical characters of interferometric SAR (InSAR) coherence. And to our knowledge, all of the existing work that related to InSAR coherence statistics, models the coherence with Gaussian distribution with no discrimination on data resolutions or scene types. Our main contribution is the investigation on the accuracies of several typical models for high resolution coherence statistics over urban areas. We select three typical land classes including trees, buildings, and shadow, as the representatives of urban areas. And different models including Gaussian, Weibull, Rayleigh, Nakagami and Beta are evaluated. Experiment results on TanDEM-X data illustrate that the Beta model reveals a better performance than other distributions. Finally, the Beta model is used in the detection of buildings.

关键词： Coherence Buildings Synthetic aperture radar Urban areas Probability density function Data models Nakagami distribution

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Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation

arXiv

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arXiv 2020年

作者： Li, Ziqiang Tao, Rentuo Niu, Hongjing Li, Bin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems University of Science and Technology of China Anhui China

Generative adversarial nets (GANs) have been successfully applied in many fields like image generation, inpainting, super-resolution and drug discovery, etc., by now, the inner process of GANs is far from been understood. To get deeper insight of the intrinsic mechanism of GANs, in this paper, a method for interpreting the latent space of GANs by analyzing the correlation between latent variables and the corresponding semantic contents in generated images is proposed. Unlike previous methods that focus on dissecting models via feature visualization, the emphasis of this work is put on the variables in latent space, i.e. how the latent variables affect the quantitative analysis of generated results. Given a pretrained GAN model with weights fixed, the latent variables are intervened to analyze their effect on the semantic content in generated images. A set of controlling latent variables can be derived for specific content generation, and the controllable semantic content manipulation be achieved. The proposed method is testified on the datasets Fashion-MNIST and UT Zappos50K, experiment results show its effectiveness. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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An ECG signal de-noising method combining the improved threshold function and ABC algorithm 3

An ECG signal de-noising method combining the improved thres...

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2022 3rd International Conference on Computer information and Big Data applications, CIBDA 2022

作者： Deng, Yanrong Huang, Yanhu School of Information and Communication Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Yulin537000 China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783800758760

Electrocardiogram (ECG) plays an imperative role in the clinical diagnosis of heart disease and heart abnormalities. In order to obtain the original ECG signal morphology, the wavelet threshold technique is usually used for ECG signal de-noising, in which threshold function and thresholds play very important role. In this paper, an improved threshold function with adjustable shape parameter was structured to improve the problems of the constant deviation in soft threshold function and the discontinuousness in hard threshold function. And then, an optimization strategy based on artificial bee colony algorithm with mean square error (MSE) as the objective function is embedded into the process of de-noising to quickly determine the optimal shape parameter and thresholds. Subsequently, a series of the simulation experiment are carried out by using two benchmark signals and real ECG signal with different noise levels. The signal-to-noise ratio (SNR) and the MSE after de-noising are used as evaluation index of the proposed method. The evaluation results demonstrate that the improved threshold function shows a better performance than the traditional threshold functions under different noise levels, and the proposed method is effective for the selections of the optimal shape parameter and thresholds in ECG signal de-noising. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Optimization

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3D Point Cloud Reconstruction of Vehicle using Inversely Mapping and Voting from CSAR Images

3D Point Cloud Reconstruction of Vehicle using Inversely Map...

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2021 CIE International Conference on Radar, Radar 2021

作者： Feng, Shanshan Lin, Yun Teng, Fei Hong, Wen Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geospatial Information Processing and Application System University of Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences Beijing China School of Electronic Information Engineering North China University of Technology Beijing China

ISBN: (纸本)9781665498142

3D reconstruction of object has raised much interest in the field of SAR. The feature of target at multi aspect angles can be obtained from sub-aperture images provided by circular SAR(CSAR), which is conducive to 3D reconstruction. Radargrammetric method is a conventional way to extract DEM while its performance for 3D reconstruction is limited by the image registration. It is difficult to find corresponding points in different sub-aperture images. In this paper, we proposed a method for 3D reconstruction of vehicle based on projections in sub-aperture images. According to the imaging mechanism of CSAR, different targets located on the same iso-range line in the zero doppler plane fall into the same cell. For a projection point, given a series of offsets, the projection point will be mapped inversely to the 3D mesh along the iso-range line. We can obtain candidates of the target. The intersection of iso-range lines can be regarded as voting process. For a candidate, the more times of intersection, the higher the number of votes, and the candidate point will be reserved. This fully excavates the information contained in the angle dimension of CSAR. The proposed approach is verified by the Gotcha Volumetric SAR Data Set. © 2021 IEEE.

关键词： Circular synthetic aperture radar(CSAR) Inversely mapping Iso-range line Three dimensional(3D) reconstruction Voting

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SALIENT SEED EXTRACTION BASED TARGET DETECTION IN SAR IMAGES

SALIENT SEED EXTRACTION BASED TARGET DETECTION IN SAR IMAGES

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IEEE International Geoscience and Remote Sensing Symposium

作者： Zongxu Pan Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

A salient seed extraction based target detection method is proposed in this paper, aiming to distinguish target points from background points in SAR images. Different from recent superpixel based method which generates superpixels firstly, and for each superpixel decides whether it belongs to part of a target. The proposed method employs a salient point to region scheme. At first, salient seeds are extracted by mean-shift and region feature based approach. Then, pixels are assigned to the most similar seed and those assigned to the salient seeds are extracted to form the foreground region. Finally, constant false alarm rate (CFAR) operation is employed to detect the target points from the foreground region. The effectiveness of the proposed method is validated by comparing with five state-of-the-art methods on TerraSAR-X images.

关键词： Target detection Salient seed extraction Synthetic aperture radar (SAR)

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