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arXiv 2024年

作者： Li, Zhuoyuan Yuan, Zikun Li, Li Liu, Dong Tang, Xiaohu Wu, Feng CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China Information Security and National Computing Grid Laboratory Southwest Jiaotong University Chengdu610031 China

In modern video coding standards, block-based inter prediction is widely adopted, which brings high compression efficiency. However, in natural videos, there are usually multiple moving objects of arbitrary shapes, resulting in complex motion fields that are difficult to represent compactly. This problem has been tackled by more flexible block partitioning methods in the Versatile Video Coding (VVC) standard, but the more flexible partitions require more overhead bits to signal and still cannot be made arbitrarily shaped. To address this limitation, we propose an object segmentation-assisted inter prediction method (SAIP), where objects in the reference frames are segmented by some advanced technologies. With a proper indication, the object segmentation mask is translated from the reference frame to the current frame as the arbitrary-shaped partition of different regions without any extra signal. Using the segmentation mask, motion compensation is separately performed for different regions, achieving higher prediction accuracy. The segmentation mask is further used to code the motion vectors of different regions more efficiently. Moreover, the segmentation mask is considered in the joint rate-distortion optimization for motion estimation and partition estimation to derive the motion vector of different regions and partition more accurately. The proposed method is implemented into the VVC reference software, VTM version 12.0. Experimental results show that the proposed method achieves up to 1.98%, 1.14%, 0.79%, and on average 0.82%, 0.49%, 0.37% BD-rate reduction for common test sequences, under the Low-delay P, Low-delay B, and Random Access configurations, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Video signal processing

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Exponential synchronization of partial-state coupled linear systems via contraction analysis

Exponential synchronization of partial-state coupled linear ...

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Annual Conference of Industrial Electronics Society

作者： Qichao Ma Ku Du Yu Kang Wei Xing Zheng Jiahu Qin Department of Automation University of Science and Technology of China Hefei China Department of Automation Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Beijing China Engineering and Mathematics Western Sydney University Sydney NSW Australia

In this paper, the contraction theory is used to analyze the synchronization for a collection of partial-state linearly coupled linear systems. First, the synchronization problem of the linear systems is transformed by defining proper error variables such that a stability problem of error systems is to be investigated. Then, the contraction analysis is performed with respect to the error system dynamics. It turns out that the error system dynamics is contracting, which in turn proves that the original systems reach synchronization exponentially fast. In addition, a brief comparison between Lyapunov method and contraction analysis is also provided. Finally, two examples are presented in order to illustrate the effectiveness of the theoretical result.

关键词： Synchronization Linear systems Trajectory Eigenvalues and eigenfunctions Symmetric matrices Lyapunov methods

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Radial Velocity Ambiguity Resolution Method in Azimuth Multichannel HRWS SAR

Radial Velocity Ambiguity Resolution Method in Azimuth Multi...

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IEEE International Conference on Radar

作者： Junying Yang Xiaolan Qiu Mingyang Shang Lihua Zhong Yini Lv Chibiao Ding Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665468893

For moving targets in synthetic aperture radar (SAR) images, the obvious features are defocusing and dislocation. To estimate motion parameters accurately is a premise for the precise imaging of moving targets. However, when the radial velocity of the target exceeds the maximum detectable unambiguous velocity, the estimated value by the existing methods is no longer the real value. A radial velocity ambiguity resolution method based on Imaging Space-Time Adaptive processing (ISTAP) is proposed in this paper. The proposed method has no search or iterative process and is suitable for the azimuth multichannel SAR with low pulse repetition frequency (PRF). Finally, the simulated data from an x-band azimuth six-channel SAR system verify the feasibility of the proposed method.

关键词： Baseband Image resolution Azimuth Energy resolution Imaging Estimation Radar imaging

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Cut-and-Fold: Automatic 3D modeling from a single image

Cut-and-Fold: Automatic 3D modeling from a single image

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Guihang Wang Xuejin Chen Si Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui China University of California San Diego La Jolla California USA

ISBN: (纸本)9781479947164

This paper presents a novel approach to automatically generate a plausible 3D model from a single outdoor image. Outdoor scene can be modeled as a set of planar billboards such as ground, sky and vertical trees or buildings. This Cut-and-Fold system takes the advantages of the statistical classification method for high-level geometric labeling of the image regions and the automatic image segmentation algorithm for detailed boundaries of the geometric regions to generate accurate geometric labeling and realistic rendering of novel views. Taking a single image as input, our method first roughly classifies each sub-region to the geometric categories: vertical, ground or sky. Then image segmentation algorithm is employed to refine the labeling results and generate accurate boundaries for the geometric regions. After cutting the image into several regions with their geometric labels, the system folds the regions into 3D billboards with accurate boundaries. The experimental results demonstrate that our method is capable of creating plausible 3D models automatically for a wide range of outdoor scenes.

关键词： Image segmentation Abstracts Labeling Indium phosphide Three-dimensional displays Solid modeling

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HIGH QUALITY REMOTE SENSING IMAGE SUPER-RESOLUTION USING DEEP MEMORY CONNECTED NETWORK

HIGH QUALITY REMOTE SENSING IMAGE SUPER-RESOLUTION USING DEE...

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IEEE International geoscience and Remote Sensing Symposium

作者： Wenjia Xu Guangluan Xu Yang Wang Xian Sun Daoyu Lin Yirong Wu Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Single image super-resolution is an effective way to enhance the spatial resolution of remote sensing image, which is crucial for many applications such as target detection and image classification. However, existing methods based on the neural network usually have small receptive fields and ignore the image detail. We propose a novel method named deep memory connected network (DMCN) based on a convolutional neural network to reconstruct high-quality super-resolution images. We build local and global memory connections to combine image detail with environmental information. To further reduce parameters and ease time-consuming, we propose down-sampling units, shrinking the spatial size of feature maps. We test DMCN on three remote sensing datasets with different spatial resolution. Experimental results indicate that our method yields promising improvements in both accuracy and visual performance over the current state-of-the-art.

关键词： spatial resolution Remote sensing Image reconstruction Training Convolutional neural networks Satellites

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A novel methodology for calculating the aerosol direct radiative effect using a non-uniform five-dimensional lookup table (Dec, 10.1080/01431161.2023.2295833, 2023)

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2024年第3期45卷 0i-0i页

作者： Shi, Zhenwei Xu, Ning Li, Jianzhong Zhang, Zhaoxu Zhao, Hui Longa, Hui Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing China School of Environmental Science and Engineering Tiangong University Tianjin China Surveying and Mapping Geographic Information Center Geological Brigade of Shandong Nuclear Industry Qingdao Shandong China

The quantification of aerosol direct radiative effects (ADREs) under clear sky conditions is essential for understanding the influence of aerosols on climate. This paper introduces a novel approach, the non-uniform five-dimensional lookup table (NU-5D-LUT) method, for calculating the ADREs under clear sky conditions. The NU-5D-LUT method considers key parameters such as aerosol optical thickness, single scattering albedo, asymmetry factor, surface albedo, and solar zenith angle. Validation against the SBDART model shows strong agreement, with correlation coefficients of 0.97 and 0.99 for TOA and BOA ADREs, respectively. Global comparisons demonstrate consistent ADRE distributions, with relative errors below 5.8% for TOA ADRE and 4.4% for BOA ADRE. The NU-5D-LUT method significantly reduces computation time, offering a practical solution for large-scale simulations and climate model evaluations in aerosol research.

关键词： Aerosol direct radiative effect aerosol optical properties lookup table

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Analysis of the Reconstruction Accuracy of Compact Polarized SAR Pseudo Quad-Pol Data for Use in Ocean Surface Observations

SSRN

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SSRN 2022年

作者： Wang, Xiaochen Hu, Yuxin Han, Bing Duan, Jitong Aerospace Information Research Institute Chinese Academy of Science Beijing100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Aerospace Information Research Institute Chinese Academy of Science Beijing100190 China Deqing Academy of Satellite Application Huzhou313200 China

This paper assesses the capability of Compact Polarized (CP) Synthetic Aperture Radar (SAR) to explore ocean surface backscattering by reconstructing the pseudo quad-pol data. Besides using Souyris’s or Nord’s algorithms, 8 scenes of Radarsat-2 quad-polarized images are used to develop an empirical model for estimating the initial value of N in Collins’ algorithm. The robustness the three published algorithms are discussed together with the reconstruction error of polarization scattering matrix [S]. The comparisons show that Collins’ algorithm is superior to the other two algorithms in terms of reconstruction errors for the hh, vv, especially, the hv channels. In addition, the influence of each algorithm on polarimetric parameters is investigated. Based on the retrieval of the polarimetric parameters, it is concluded that Souyris’s, Nord’s and Collins’ algorithms all have similar (high) accuracies for co-polarization backscattering coefficient σ0HH, σ0VV, co-polarization correlation coefficient ρ and first eigenvalue l1, while for cross-polarization backscattering coefficient σ0HV and scattering angle α, the accuracy of Collins’ algorithm is better than that of Souyris’s or Nord’s’. Although all three algorithms produced low accuracies for second eigenvalue l2, third eigenvalue l3, scattering entropy H and scattering anisotropy A, the results obtained using Collins’ algorithm were better than those produced by the other two algorithms. © 2022, The Authors. All rights reserved.

关键词： Synthetic aperture radar

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Automated ortho-rectified SAR image of GF-3 satellite using Reverse-Range-Doppler method

Automated ortho-rectified SAR image of GF-3 satellite using ...

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IEEE International Symposium on geoscience and Remote Sensing (IGARSS)

作者： Jiayin Liu Xiaolan Qiu Wen Hong Institute of Electronics Chinese Academy of Sciences Beijing China Key Laboratory of Technology on Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Beijing China

GF-3 is the Chinese Synthetic Aperture Radar (SAR) satellite mission with scientific and commercial applications, which will be launched in 2016. The ortho-rectification image combined with the DEM data can only be satisfied with the applications of the high resolution radar image, the data quantity with wide-breadth also put forward higher request to the automation processing. The Reverse-Range-Doppler method was used to ortho-rectified the SAR image of GF-3 satellite based on the Range-Doppler model in this paper. It not only ensures the correction precision, but also simplifies the iteration steps about DEM data, and improves the efficiency of automatic processing.

关键词： Synthetic aperture radar Mathematical model Satellites Doppler effect Space vehicles Earth Azimuth

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A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective

arXiv

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arXiv 2021年

作者： Li, Xin Jin, Xin Fu, Jun Yu, Xiaoyuan Tong, Bei Chen, Zhibo The CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China The Eastern Institute for Advanced Study China Huawei Cloud China

Collecting amounts of distorted/clean image pairs in the real world is non-trivial, which seriously limits the practical applications of these supervised learning-based methods on real-world image super-resolution (RealSR). Previous works usually address this problem by leveraging unsupervised learning-based technologies to alleviate the dependency on paired training samples. However, these methods typically suffer from unsatisfactory texture synthesis due to the lack of supervision of clean images. To overcome this problem, we are the first to have a close look at the under-explored direction for RealSR, i.e., few-shot real-world image super-resolution, which aims to tackle the challenging RealSR problem with few-shot distorted/clean image pairs. Under this brand-new scenario, we propose Distortion Relation guided Transfer Learning (DRTL) for the few-shot RealSR by transferring the rich restoration knowledge from auxiliary distortions (i.e., synthetic distortions) to the target RealSR under the guidance of distortion relation. Concretely, DRTL builds a knowledge graph to capture the distortion relation between auxiliary distortions and target distortion (i.e., real distortions in RealSR). Based on the distortion relation, DRTL adopts a gradient reweighting strategy to guide the knowledge transfer process between auxiliary distortions and target distortions. In this way, DRTL could quickly learn the most relevant knowledge from the synthetic distortions for the target distortion. We instantiate DRTL with two commonly-used transfer learning paradigms, including pre-training and meta-learning pipelines, to realize a distortion relation-aware Few-shot RealSR. Extensive experiments on multiple benchmarks and thorough ablation studies demonstrate the effectiveness of our DRTL. Copyright © 2021, The Authors. All rights reserved.

关键词： Textures

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Sequential reinforced 360-degree video adaptive streaming with cross-user attentive network

arXiv

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arXiv 2020年

作者： Fu, Jun Chen, Zhibo Chen, Xiaoming Li, Weiping CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China School of Computer Science and Engineering Beijing Technology and Business University China

In the tile-based 360-degree video streaming, predicting user’s future viewpoints and developing adaptive bitrate (ABR) algorithms are essential for optimizing user’s quality of experience (QoE). Traditional single-user based viewpoint prediction methods fail to achieve good performance in long-term prediction, and the recently proposed reinforcement learning (RL) based ABR schemes applied in traditional video streaming can not be directly applied in the tile-based 360-degree video streaming due to the exponential action space. Therefore, we propose a sequential reinforced 360-degree video streaming scheme with cross-user attentive network. Firstly, considering different users may have the similar viewing preference on the same video, we propose a cross-user attentive network (CUAN), boosting the performance of long-term viewpoint prediction by selectively utilizing cross-user information. Secondly, we propose a sequential RL-based (360SRL) ABR approach, transforming action space size of each decision step from exponential to linear via introducing a sequential decision structure. We evaluate the proposed CUAN and 360SRL using trace-driven experiments and experimental results demonstrate that CUAN and 360SRL outperform existing viewpoint prediction and ABR approaches with a noticeable margin. Copyright © 2020, The Authors. All rights reserved.

关键词： Forecasting

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