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检索条件"任意字段=Conference on Image and Signal Processing for Remote Sensing IX"

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Human-computer Interactive System Development for Cloud Removal from Single images 7

Human-computer Interactive System Development for Cloud Remo...

引用

conference on Optical Metrology and Inspection for Industrial Applications VII

作者： Wu, Feng Zhu, Xifang Xiang, Ruxi Xu, Qingquan Xu, Yang Sun, Qingcheng Changzhou Inst Technol Sch Elect & Informat Engn 666 Liaohe Rd Changzhou 213032 Jiangsu Peoples R China

ISBN: (数字)9781510639201

ISBN: (纸本)9781510639201

remote sensing imaging is disturbed by clouds frequently and produces images with low contrast and poor resolution. Algorithms removing clouds from single remote sensing images are expected to improve their qualities and aroused worldwide interests. Compared with multi-image methods, cloud removal algorithms from single images reduce the demands for weather and improve the image collecting flexibility. In this paper, a human-computer interactive system for cloud removal from single images was developed according to the proposed cloud removal algorithm. Firstly, the distributions of clouds and sceneries in the contaminated remote sensing images were discussed. Features of the dual tree complex wavelet transform (DTCWT) to split image frequencies were investigated after the principle of DTCWT was analyzed. By combining the frequency features of DTCWT sub-bands and the frequency distributions of the remote sensing images, the cloud removal algorithm based on DTCWT was proposed, and its procedures were described completed. Then, a human-computer interactive system for cloud removal was developed in order to improve the cloud removal processing conveniences and achieve the best performance. The development schemes were introduced. The system structures were illustrated. The design methods of the camera driver and video signal output program were described. Communication streams between modules and human-computer interaction interfaces were designed further according to the cloud removal algorithm based on DTCWT. The system has a very good flexibility which permits the input of most parameters from users and is expect to achieve a best performance. Finally, the device of the system was completed and tested. image acquisition and cloud removal processing experiments were implemented by applying the human-computer interactive system. Cloud removal effects by adjusting parameters through the human-computer interaction interfaces were compared and evaluated. It proved that th

关键词： cloud removal dual tree complex wavelet transform human-computer interaction remote sensing image

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IEEE International conference on Acoustics, Speech and signal processing

作者： Zhinan Cai Zhiyu Jiang Yuan Yuan School of Computer Science and School of Artificial Intelligence Optics and Electronics (iOPEN) Northwestern Polytechnical University Xi’an P. R. China

Change detection for remote sensing images is widely applied for urban change detection, disaster assessment and other fields. However, most of the existing CNN-based change detection methods still suffer from the problem of inadequate pseudo-changes suppression and insufficient feature representation. In this work, an unsupervised change detection method based on Task-related Self-supervised Learning Change Detection network with smooth mechanism(TSLCD) is proposed to eliminate it. The main contributions include: (1) the task-related self-supervised learning module is introduced to extract spatial features more effectively. (2) a hard-sample-mining loss function is applied to pay more attention to the hard-to-classify samples. (3) a smooth mechanism is utilized to remove some of pseudo-changes and noise. Experiments on four remote sensing change detection datasets reveal that the proposed TSLCD method achieves the state-of-the-art for change detection task.

关键词： conferences signal processing Feature extraction Acoustics Sensors Task analysis Speech processing

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DOVE: Decomposition Oriented Video super-rEsolution

DOVE: Decomposition Oriented Video super-rEsolution

引用

IEEE International conference on Visual Communications and image processing (VCIP)

作者： Wang, Huairui Sun, Wanjie Chen, Zhenzhong Yang, Daiqin Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China

ISBN: (纸本)9781728180687

Video super-resolution (VSR) has attracted a lot of attention that converts a low resolution (LR) video into a high resolution (HR) one. The original LR video is typically produced either by the downscaling processing or low-resolution sensor. Considering that the resolution degradation or limitation makes different impacts on different low-frequency (LF) and high-frequency (HF) components of the LR video signal, we propose a Decomposition Oriented Video super-rEsolution (DOVE) method in this paper. More specifically, a three-stream VSR network is designed in which the proposed LF and HF stream is responsible for modeling LF and HF components in the feature space. Moreover, a multi-frame refinement stream takes features of coarsely aligned frames as input and generates finely aligned counterparts progressively to guide the learning of LF and HF streams at the intermediate feature level. Furthermore, non-local channel attention is devised to capture long-range dependencies on a global scale both in the channel domain. Experimental results indicate that separating the learning of LF and HF components helps better estimate the HR frame from LR frames and superior VSR performance is achieved when compared with that of recent state-of-the-art methods.

关键词： video super-resolution feature decomposition deformable convolution non-local attention

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Feature and information extraction for regions of Southeast Europe from Corona satellite images acquired in 1968 8

Feature and information extraction for regions of Southeast ...

引用

8th International conference on remote sensing and Geoinformation of the Environment (RSCy)

作者： Dimitris Stratoulias Kabadayi, M. Erdem Ton Duc Thang Univ Informetr Res Grp Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Appl Sci Ho Chi Minh City Vietnam Koc Univ Rumelifeneri Yolu TR-34450 Istanbul Turkey

ISBN: (纸本)9781510638570;9781510638587

The Corona spy programme was a series of reconnaissance satellites which delivered more than 860000 images between 1960 and 1972. Since 1995, the data are declassified and a large historic earth observation archive is made accessible to the scientific community. Despite the large volume of information and the high spatial resolution of the satellite imagery, little has been done in the last 25 years in the context of image processing of this data source, a fact which perhaps can be attributed to the technical difficulties of these primitive images such as the lack of metadata, intense spatial and radiometric distortions, low signal-to-Noise Ratio (SNR) and a single panchromatic band. Hence, the photogrammetric challenges to extract useful information are paramount. In this study, we present recent developments arising from our efforts to map settlements and agricultural parcels over the Plovdiv region, Bulgaria from a Corona image acquired in 1968. We, overall, present initial findings from the integration of earth observation into the ERC-StG project UrbanOccupationsOETR and evaluate the usability of such primitive images in feature extraction. We compare the areas corresponding to settlements and correlate them with concurrent population census. Based on the findings, we suggest that settlements and agricultural parcels can be mapped from a Corona KH-4B image with fine radiometric quality.

关键词： remote sensing historical GIS Corona feature extraction segmentation settlements agriculture

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SEMI-SUPERVISED MULTI-SPECTRAL LAND COVER CLASSIFICATION WITH MULTI-ATTENTION AND ADAPTIVE KERNEL

SEMI-SUPERVISED MULTI-SPECTRAL LAND COVER CLASSIFICATION WIT...

引用

IEEE International conference on image processing (ICIP)

作者： Zhang, Kexin Yang, Hua Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China Shanghai Key Lab Digital Media Proc & Transmiss Shanghai Peoples R China

ISBN: (纸本)9781728163956

Land cover classification is one vital and challenging task in remote sensing (RS) field. Tackling the limited labeled training data and for exploiting abundant information of multi-spectral bands, we proposed a novel semi-supervised multi-spectral classification network with multi-attention and adaptive kernel. We select 10 land cover related bands and combine them into different spectral groups. To further extract discriminating feature in spectral and spatial dimension, we design one multi-attention block. Furthermore, the adaptive receptive field mechanism is introduced to dynamically adjust kernel size in convolution layer and aggregate multi-scale information. Experiments on EuroSAT dataset demonstrate that the proposed method can outperform greatly state-of-the-art methods, especially when the number of labeled data is relatively small.

关键词： Multi-Spectral Land Cover Classification Semi-Supervised Adaptive Kernel Multi-Attention

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Research on Automatic Target Tracking Technology Based on remote sensing Video Data 6th

Research on Automatic Target Tracking Technology Based on Re...

引用

6th conference on signal and Information processing, Networking and Computers, ICSINC 2019

作者： Yu, Zhicheng Li, Tao Liu, Ke Beijing Institute of Space Mechanics and Electricity Beijing100094 China

ISBN: (纸本)9789811541629

Recent years, with the rapidly development of aerospace remote sensing technology and commercial aerospace, the resolution of aerospace remote sensor has been improved continuously. Accordingly, it is possible to identify and track targets based on space remote sensing data. Furthermore, the corresponding application demands of various industries have also increased. In this paper, a new framework of target detection and automatic tracking technology based on remote sensing video data is put forward. Variation detection and the detection and tracking of moving targets are carried out with the data frame difference technology. In addition, the influences of channel detection on different frame tracking are analyzed in detail. Finally, the experiments of precise tracking for various remote sensing image data are also carried out. It is shown from the experiment that the proposed method can perform good detection effects. Moreover, as for the remote sensing video data, the problems of target tracking can also be efficiently solved, especially those for slow-moving targets and the target tracking with long frame intervals. © 2020, Springer Nature Singapore Pte Ltd.

关键词： remote sensing

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Automatic Cloud Detection in Resourcesat LISS-3 Data using Spectral Angle Similarity and Mode Seeking Reference Spectra 15

Automatic Cloud Detection in Resourcesat LISS-3 Data using S...

引用

15th IEEE International conference on Industrial and Information Systems, ICIIS 2020

作者： Misra, Indranil Manthira Moorthi, S. Dhar, Debajyoti Signal and Image Processing Group Space Applications Centre Indian Space Research Organisation Ahmedabad India

ISBN: (纸本)9781728185248

Optical remote sensing images contain cloud pixels, which need to be detected and masked for different earth observation studies and applications. In literature, various algorithms are reported which can detect cloud in multi-spectral remote sensing images. In this paper, we have developed an approach based on spectral angle computation that measures the radiometric gap between a reference pixel and input image pixels. Reference spectra is determined using mode seeking technique by taking multiple cloud pixels from multi-temporal images covering different land terrain. The processing chain is developed and tested in Resourcesat LISS-3 surface reflectance data. Result section shows that technique developed can determine thick cloud pixels with high confidence interval and compared with other novel cloud detection methods. © 2020 IEEE.

关键词： Pixels

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Land Cover Classification and Accuracy Evaluation Based on Object-Oriented Spatial Features of GF-2 15th

Land Cover Classification and Accuracy Evaluation Based on O...

引用

15th EAI International conference on Communications and Networking, ChinaCom 2020

作者： Chen, Xiaomao Li, Jiakun Li, Yuanfa Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin University of Electronic Technology Guilin541004 China National and Local Joint Engineering Research Center of Satellite Navigation Positioning and Location Service Guilin541004 China

ISBN: (纸本)9783030677190

The urbanization process has changed urban land, which has affected the environmental quality of urban residents. It is very important to obtain urban land cover information. In this paper, Yangshuo, a small country of Guilin City, is used as the research area, and the object-oriented spatial feature extraction module (Feature Extraction, hereinafter referred to as FX) is used to carry out experiments and accuracy evaluation of land cover classification in the research area. Extracting land cover information from the GF-2 remote sensing image, establishing a classification system sample based on the characteristic information of six land cover classification objects such as urban land, waterbody, woodland, farmland, road and other lands, and finally execute Supervising the classification and verify its accuracy. The results show that this method can recognize the land cover accurately and the total accuracy verified is as high as 97.41%. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Classification (of information)

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Towards Quantized DCT Coefficients Restoration for Compressed images

Towards Quantized DCT Coefficients Restoration for Compresse...

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IEEE International conference on Visual Communications and image processing (VCIP)

作者： Ouyang, Tong Chen, Zhenzhong Liu, Shan Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China Tencent Media Lab Palo Alto CA USA

ISBN: (纸本)9781728180687

images and videos suffer from undesirable visual artifacts at high compression ratios, which is due to the use of the discrete cosine transform and scalar quantization in the compression. To restore the quantized coefficients via producing the quantization error, we propose a coefficients restoration convolutional neural network in the frequency domain (FD-CRNet). Taking advantage of residual learning, the proposed FD-CRNet efficiently exploits the related distribution of different frequency components. The squeeze-and-excitation block (SE block) is adopted to reduce the computational complexity and better restoration performance. Experimental results show the quantized coefficients are recovered near the lossless coefficients effectively, which outperforms the existed coefficients restoration methods. In addition, the performance of methods in the spatial domain is significantly i mproved b y F D-CRNet w ith m ore authentic details and sharper edges when removing the compression artifacts.

关键词： Coefficients r estoration i mage restoration quantization noise

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DEFORMABLE SPATIAL PROPAGATION NETWORKS FOR DEPTH COMPLETION

DEFORMABLE SPATIAL PROPAGATION NETWORKS FOR DEPTH COMPLETION

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IEEE International conference on image processing (ICIP)

作者： Xu, Zheyuan Yin, Hongche Yao, Jian Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China Shenzhen Jimuyida Technol Co Ltd Shenzhen Peoples R China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163956

Depth completion has attracted extensive attention recently due to the development of autonomous driving, which aims to recover dense depth map from sparse depth measurements. Convolutional spatial propagation network (CSPN) is one of the state-of-the-art methods in this task, which adopt a linear propagation model to refine coarse depth maps with local context. However, the propagation of each pixel occurs in a fixed receptive field. This may not be the optimal for refinement since different pixel needs different local context. To tackle this issue, in this paper, we propose a deformable spatial propagation network (DSPN) to adaptively generates different receptive field and affinity matrix for each pixel. It allows the network obtain information with much fewer but more relevant pixels for propagation. Experimental results on KITTI depth completion benchmark demonstrate that our proposed method achieves the state-of-the-art performance.

关键词： depth completion deformable spatial propagation KITTI dataset

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