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arXiv 2019年

作者： Chen, Zhibo Xu, Jiahua Lin, Chaoyi Zhou, Wei CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China

Objective quality assessment of stereoscopic omnidirectional images is a challenging problem since it is influenced by multiple aspects such as projection deformation, field of view (FoV) range, binocular vision, visual comfort, etc. Existing studies show that classic 2D or 3D image quality assessment (IQA) metrics are not able to perform well for stereoscopic omnidirectional images. However, very few research works have focused on evaluating the perceptual visual quality of omnidirectional images, especially for stereoscopic omnidirectional images. In this paper, based on the predictive coding theory of the human vision system (HVS), we propose a stereoscopic omnidirectional image quality evaluator (SOIQE) to cope with the characteristics of 3D 360-degree images. Two modules are involved in SOIQE: predictive coding theory based binocular rivalry module and multi-view fusion module. In the binocular rivalry module, we introduce predictive coding theory to simulate the competition between high-level patterns and calculate the similarity and rivalry dominance to obtain the quality scores of viewport images. Moreover, we develop the multi-view fusion module to aggregate the quality scores of viewport images with the help of both content weight and location weight. The proposed SOIQE is a parametric model without necessary of regression learning, which ensures its interpretability and generalization performance. Experimental results on our published stereoscopic omnidirectional image quality assessment database (SOLID) demonstrate that our proposed SOIQE method outperforms state-of-the-art metrics. Furthermore, we also verify the effectiveness of each proposed module on both public stereoscopic image datasets and panoramic image datasets. Copyright © 2019, The Authors. All rights reserved.

关键词： Binocular vision

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Online filter clustering and pruning for efficient convnets

arXiv

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arXiv 2019年

作者： Zhou, Zhengguang Zhou, Wengang Hong, Richang Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System EEIS Department University of Science and Technology of China HeFei University of Technology

Pruning filters is an effective method for accelerating deep neural networks (DNNs), but most existing approaches prune filters on a pre-trained network directly which limits in acceleration. Although each filter has its own effect in DNNs, but if two filters are same with each other, we could prune one safely. In this paper, we add an extra cluster loss term in the loss function which can force filters in each cluster to be similar online. After training, we keep one filter in each cluster and prune others and fine-tune the pruned network to compensate the loss. Particularly, the clusters in every layer can be defined firstly which is effective for pruning DNNs within residual blocks. Extensive experiments on CIFAR10 and CIFAR100 benchmarks demonstrate the competitive performance of our proposed filter pruning method. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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A cloaking-based approach to protect location privacy in location-based services 33

A cloaking-based approach to protect location privacy in loc...

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Proceedings of the 33rd Chinese Control Conference, CCC 2014

作者： Zheng, Jiangyu Tan, Xiaobin Zou, Cliff Niu, Yukun Zhu, Jin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei230026 China Department of Automation University of Science and Technology of China Hefei230026 China Department of Electrical Engineering and Computer Science University of Central Florida OrlandoFL32816-2362 United States

ISBN: (纸本)9789881563842

With the widespread use of mobile devices, the location-based service (LBS) applications become increasingly popular, which introduces the new security challenge to protect user's location privacy. On one hand, a user expects to report his own location as far as possible away from his real location to protect his location privacy. On the other hand, in order to obtain high quality of service (QoS), users are required to report their locations as accurate as possible. To achieve the dedicated tradeoff between privacy requirement and QoS requirement, we propose a novel approach based on cloaking technique. We also discuss the disadvantage of the traditional general system model and propose an improved model. The basic idea of our approach is to select a sub-area from the generated cloaking area as user's reported location. The sub-area may not contain a user's real location, which prevents an adversary from performing attack with side information. Specifically, by defining an objective function with a novel location privacy metric and a QoS metric, we are able to convert the privacy issue to an optimization problem. Then, location privacy metric and QoS metric are given. To reduce the complexity of the optimization, a heuristic algorithm is proposed. Through privacy-preserving analysis and comparison with related work [8], we demonstrate the effectiveness and efficiency of our approach. © 2014 TCCT, CAA.

关键词： Location based services

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Analysis of designed composite scatterer on high resolution PolSAR image

Analysis of designed composite scatterer on high resolution ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Hu Ding-sheng Qiu Xiao-Ian Li Fang-fang Ding Chi-Biao Institute of Electronics Chinese Academy of Sciences (IECAS) Beijing China University of Chinese Academy of Sciences (UCAS) Beijing China Key Laboratory of Technology on Geo-spatial Information Processing and Application System Beijing 100190 China Key Laboratory of Technology on Geo-spatial Information Processing and Application System Beijing China

Multiple scattering may render synthetic aperture radar (SAR) image interpretation difficult, particularly when it comes to imaging of man-made structures, which can be modeled as composite scatterers. To isolate different scattering mechanism, we designed an airborne SAR experiment based on the high resolution, sub-metric to decimetric range, capabilities full-polarimetric SAR system, CARSS (Chinese Airborne Remote Sensing system), developing by IECAS. The imaging results are quite accord with the theoretical analysis. With polarimetric target decomposition, we can simply distinguish the different scattering mechanism. The idea to interpret the man-made targets as the combination of simple scattering mechanisms is supported by the experiment results.

关键词： Scattering Synthetic aperture radar Imaging Image color analysis Image resolution Radar imaging Remote sensing

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Repeat-pass SAR interferometry experiments with gaofen-3: A case study of ningbo area

arXiv

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arXiv 2017年

作者： Zhang, Tao Lv, Xiaolei Han, Bing Lei, Bin Hong, Jun Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

This paper reports the repeat-pass interferometric SAR results of Gaofen-3, a Chinese civil SAR satellite, acquired in November 2016 and March 2017 from Ningbo area. With the spatial baseline about 600 m and time baseline 116 days, the coherence of the two images still achieve good enough to generate the digital elevation model (DEM). During the InSAR processing, we compared several baseline estimating methods and obtained a good flat-earth phase removed interferogram map. By using the latest SAR interferogram filter and phase unwrapping method we proposed, we improved the coherence up to 0.8 in urban area and obtained a high quality DEM in Ningbo area. In addition, we evaluated the elevation model by comparing with the elevation values extracted from SRTM. And the result shows that accuracy of the elevation map is about 5 m (RMS) in plane area and is about 22m (RMS) in mountainous region, which demonstrated that Gaofen-3 has the powerful ability of repeat-pass SAR Interferometry. Copyright © 2017, The Authors. All rights reserved.

关键词： Surveying

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The shadow enhancement for targets with flat structures in SAR images

The shadow enhancement for targets with flat structures in S...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yueting Zhang Xiaolan Qiu Bin Lei Kun Fu Fangfang Li Chibiao Ding Key Laboratory of Geo-spatial Information Processing and Application System Technology Chinese Academy of Sciences Institute of Electronics Chinese Academy of Science

The edges of the shadow region are blurred in the SAR image due to the moving of the radar during data collection. This phenomenon becomes obvious in the High Resolution SAR images. Shadow enhancement is of great value for ATR especially when the scattering centers of the target itself are not clear. In this paper, an approach for shadow enhancement in the SAR images for targets with plat structures is presented. And experiments on the Mini-SAR data test the validity of the approach.

关键词： Synthetic aperture radar Scattering Azimuth Image edge detection Automotive components Radar imaging

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RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS for DEEP SEMANTIC IMAGE SEGMENTATION USING MULTI-MODAL DATA

RESIDUAL SHUFFLING CONVOLUTIONAL NEURAL NETWORKS for DEEP SE...

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2018 ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020"

作者： Chen, K. Weinmann, M. Gao, X. Yan, M. Hinz, S. Jutzi, B. Weinmann, M. Key Laboratory of Spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Institute of Computer Science II University of Bonn Bonn Germany Institute of Photogrammetry and Remote Sensing Karlsruhe Institute of Technology Karlsruhe Germany

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation. © 2018 Copernicus GmbH. All rights reserved.

关键词： Aerial Imagery CNN Deep Learning Multi-Modal Data Residual Network Semantic Segmentation

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A Differentiable Framework for Image-Based SAR Target Reconstruction with 3D Gaussian Splatting

A Differentiable Framework for Image-Based SAR Target Recons...

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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Zinan Liu Shengren Niu Xiaolan Qiu Lingxiao Peng Lihua Zhong Chibiao Ding The National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Aerospace Information Research Institute Chinese Academy of Sciences Suzhou China Key Laboratory of Technology in Geospatial Information Processing and Application Systems Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Image-based synthetic aperture radar (SAR) target three-dimensional (3D) reconstruction is an important application for extracting target information from high-resolution two-dimensional (2D) SAR images. However, due to the complex mechanism of SAR imaging, developing a data-driven, fully automated 3D reconstruction framework with explicit physical constraints is very difficult. Thus, this paper proposes a differentiable framework for image-based SAR target reconstruction with 3D Gaussian Splatting, which can automatically realize the 3D target reconstruction from multi-view SAR images. Specifically, the proposed differentiable framework accumulates and generates simulated SAR images according to the SAR imaging geometry and projection during the forward simulation stage. By calculating the loss between the simulated and ground truth SAR images and backpropagating, the spatial positions of the 3D Gaussians are continuously adjusted until convergence, generating the 3D point cloud model of the target. The experiment is conducted on the constructed T72 SAR image dataset and the reconstruction results demonstrate the effectiveness of the proposed framework.

关键词： Point cloud compression Geometry Solid modeling Three-dimensional displays Two-dimensional displays Data processing Radar polarimetry Robustness Image reconstruction Synthetic aperture radar

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A Simple Topographic Correction Method Based on Smoothed Terrain

A Simple Topographic Correction Method Based on Smoothed Ter...

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International Symposium on Image and Data Fusion (ISIDF)

作者： Kang Jiang Yong-chao Zhao Xiu-rui Geng Key Laboratory of Technology in Geo-spatial information Processing and Application System Institute of Electronics Chinese Academy of Sciences (IECAS) Beijing China

A simple topographic correction method based on smoothed terrain is proposed in this paper. The main idea of the new method is smoothing the slope angle of terrain in the first place and then performing the cosine correction based on the smoothed terrain. The smoothing effect on the terrain is significant in forested mountainous areas and a model is proposed to explain the effect physically. A comparison is conducted among the new method and several other common methods like C, SCS, Minnaert corrections using Landsat-7 ETM+ data in Shanxi Province in China. Visual analysis and statistical analysis are adopted to assess the performance of these methods from two aspects: overcorrection, homogeneity within a land cover class. Comparison results indicate that the smoothing step can significantly reduce the overcorrection and the performance of the new method is on the same level with C correction. The new method does not require any training data from image to obtain parameters and proves to be an effective and simple method in forested areas.

关键词： Remote sensing Smoothing methods Satellites Visualization Surfaces Optical sensors Adaptive optics

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Cause analysis for the blurring phenomenon of shadow edges in terms of SAR imaging algorithms

Cause analysis for the blurring phenomenon of shadow edges i...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Qi Liu Yueting Zhang Xiaolan Qiu Wenlong Hu University of Chinese Academy of Sciences Beijing China Key Laboratory of Spatial Information Processing and Application System Technology IECAS Beijing China

ISBN: (纸本)9781467372985

The shadow is a particular phenomenon in SAR images, inflecting some information of the target. However, the shadow edges are blurred in SAR images. Thus, we analyze the causes for the blurring phenomenon of shadow edges in terms of SAR imaging algorithms in this paper. Taking the range Doppler algorithm for example, we conduct four simulation experiments to compensate for different processing steps and compare the imaging discrepancy among the refocused shadow edges. The conclusions are that the blurring phenomenon of shadow edges in SAR images is mainly reflected in azimuth, and azimuth compression is the major impact-factor to the shadow imaging quality. It is obvious that optimization of azimuth compression should get more attention for shadow enhancement in SAR images.

关键词： Synthetic aperture radar Azimuth Imaging Image edge detection Radar imaging Image resolution Radar polarimetry

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