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Non-reference virtual view quality evaluation of MVD

Journal of Shanghai University(English Edition) 2011年第4期15卷 342-346页

作者：张艳安平张秋闻王元庆张兆杨 School of Communication and Information Engineering Shanghai University Department of Computer Science and Technology Anhui University of Finance and EconomicsBengbu 230030AnhuiP.R.China Key Laboratory of Advanced Display and System Application (shanghai University) Ministry of Education Department of Electronics Science and Engineering Nanjing University

The quality of virtual view based on multi-view video （MVD） plus depth format is often evaluated by PSNR or subjectively judged. However, due to synthesizing arbitrary view images, the virtual view images mostly have no reference images and are only assessed using non-reference. Virtual view images synthesized by depth estimation reference software （DERS） and view synthesis reference software （VSRS） often accompanied with blockiness and other distortions on the edge. In addition, matching level for the depth map and the corresponding texture maps of left and right views also affects the quality of the virtual view. This paper compares the edge similarity of the depth and the corresponding texture maps which generate the intermediate virtual view and combined with the virtual view＇s blockiness which causing blur to evaluate the quality of the virtual view. Experiment results show that the proposed method can reflect the quality of the virtual view better.

关键词： non-reference quality evaluation virtual view multi-view video （MVD） plus depth free viewpoint television （FTV）

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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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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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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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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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Quantum-behaved PSO-based Lyapunov control of closed quantum systems

Quantum-behaved PSO-based Lyapunov control of closed quantum...

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第40届中国控制会议

作者： Song Liu Sen Kuang Department of Automation University of Science and Technology of China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

A Lyapunov-based control scheme is presented to drive closed quantum systems into any target eigenstate with as high population as possible by the quantum-behaved particle swarm optimization（PSO） algorithm. Based on a Lyapunov function with a Hermitian operator to be constructed, a control law with the unknown parameters contained in the Hermitian operator is designed. To achieve high-population state transfer to the target state, we first initialize those unknown parameters by choosing a path to the target state in its energy-level connectivity graph and setting their values along the path. Then, a set of optimal parameters is found by the quantum-behaved PSO algorithm. Finally, numerical simulation experiments are performed on a five-level quantum system and a four-qubit system to demonstrate the effectiveness of the control scheme in this paper.

关键词： Quantum systems Lyapunov control quantum-behaved PSO algorithm energy-level connectivity graph high-population transfer

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Optimization approach for multi-scale segmentation of remotely sensed imagery under k-means clustering guidance

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Cehui Xuebao/Acta Geodaetica et Cartographica Sinica 2015年第5期44卷 526-532页

作者： Wang, Huixian Jin, Huijia Wang, Jiaolong Jiang, Wanshou State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China Hebei Provincial Institute of Cartography Shijiazhuang050031 China

In order to adapt different scale land cover segmentation, an optimized approach under the guidance of k-means clustering for multi-scale segmentation is proposed. At first, small scale segmentation and k-means clustering are used to process the original images;then the result of k-means clustering is used to guide objects merging procedure, in which Otsu threshold method is used to automatically select the impact factor of k-means clustering;finally we obtain the segmentation results which are applicable to different scale objects. FNEA method is taken for an example and segmentation experiments are done using a simulated image and a real remote sensing image from GeoEye-1 satellite, qualitative and quantitative evaluation demonstrates that the proposed method can obtain high quality segmentation results. ©, 2015, SinoMaps Press. All right reserved.

关键词： Remote sensing

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Journal of Computational information systems 2014年第17期10卷 7259-7267页

作者： Qi, Xiang Wu, Wei Huang, Yu Huang, Tinglei Fu, Kun Wang, Hongqi Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics University of Chinese Academy of Sciences Beijing China University of Science and Technology of China Hefei China

In this paper we propose the rating Correlated Topic Model for rating-based collaborative filtering, which improves the performance of the state-of-the-art Latent Semantic Models in two aspects: (1), making the prediction accuracy more robust to the topic number K;(2), improving the recommendation quality for users with few existed ratings. We achieve our goals by employing the Logistic Normal distribution to capture the correlation between latent topics following the Correlated Topic Model, as well as modifying the generative process to meet the requirement of rating-based collaborative filtering. We derive a parameter estimation algorithm based on variational inference for the proposal. Experiment results on the Movielens data set demonstrate our model's advantages on both referred aspects.

关键词： Collaborative filtering

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Offline and Online Optical Flow Enhancement for Deep Video Compression

arXiv

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arXiv 2023年

作者： Tang, Chuanbo Sheng, Xihua Li, Zhuoyuan Zhang, Haotian Li, Li Liu, Dong CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei230027 China

Video compression relies heavily on exploiting the temporal redundancy between video frames, which is usually achieved by estimating and using the motion information. The motion information is represented as optical flows in most of the existing deep video compression networks. Indeed, these networks often adopt pre-trained optical flow estimation networks for motion estimation. The optical flows, however, may be less suitable for video compression due to the following two factors. First, the optical flow estimation networks were trained to perform inter-frame prediction as accurately as possible, but the optical flows themselves may cost too many bits to encode. Second, the optical flow estimation networks were trained on synthetic data, and may not generalize well enough to real-world videos. We address the twofold limitations by enhancing the optical flows in two stages: offline and online. In the offline stage, we fine-tune a trained optical flow estimation network with the motion information provided by a traditional (non-deep) video compression scheme, e.g. H.266/VVC, as we believe the motion information of H.266/VVC achieves a better rate-distortion tradeoff. In the online stage, we further optimize the latent features of the optical flows with a gradient descent-based algorithm for the video to be compressed, so as to enhance the adaptivity of the optical flows. We conduct experiments on a state-of-the-art deep video compression scheme, DCVC. Experimental results demonstrate that the proposed offline and online enhancement together achieves on average 12.8% bitrate saving on the tested videos, without increasing the model or computational complexity of the decoder side. Copyright © 2023, The Authors. All rights reserved.

关键词： Image coding

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A Hybrid and Explainable Deep Learning Framework for SAR Images

A Hybrid and Explainable Deep Learning Framework for SAR Ima...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Zhongling Huang Mihai Datcu Zongxu Pan Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System CAS Remote Sensing Technology Institute (IMF) German Aerospace Center (DLR)

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Deep learning based patch-wise Synthetic Aperture Radar (SAR) image classification usually requires a large number of labeled data for training. Aiming at understanding SAR images with very limited annotation and taking full advantage of complex-valued SAR data, this paper proposes a general and practical framework for quad-, dual-, and single-polarized SAR data. In this framework, two important elements are taken into consideration: image representation and physical scattering properties. Firstly, a convolutional neural network is applied for SAR image representation. Based on time-frequency analysis and polarimetric decomposition, the scattering labels are extracted from complex SAR data with unsupervised deep learning. Then, a bag of scattering topics for a patch is obtained via topic modeling. By assuming that the generated scattering topics can be regarded as the abstract attributes of SAR images, we propose a soft constraint between scattering topics and image representations to refine the network. Finally, a classifier for land cover and land use semantic labels can be learned with only a few annotated samples. The framework is hybrid for the combination of deep neural network and explainable approaches. Experiments are conducted on Gaofen-3 complex SAR data and the results demonstrate the effectiveness of our proposed framework.

关键词： Deep learning Training Annotations Scattering Image representation Radar polarimetry Synthetic aperture radar

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