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An improved anti-noise FCM algorithm incorporating spatial information for image segmentation

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An improved anti-noise FCM algorithm incorporating spatial i...

Digital humanities affect: The evolution and revolution of spatial information organization in science fiction

第六届全国几何设计与计算学术会议

作者： ZHENG Fu-Hua LIU Yi ZHANG Xiao-Feng ZHANG Ling ZHANG Cai-Ming Department of Computer Science and Technology Shandong University Department of Computer Science and Technology Shandong University of Finance and Economics Shandong Provincial Key Laboratory of Digital Media Technology

Standard fuzzy c-means (FCM) algorithm does not consider spatial neighborhood information in the process of clustering, which makes it sensitive to noise and cannot achieve satisfying results for image segmentation. In order to reduce the noise effect during segmentation, we present an improved anti-noise FCM algorithm by incorporating a neighborhood term into the standard FCM algorithm. The neighborhood term combines the relative location information and gray level information of the neighboring pixels. It can control the influence of the neighboring pixels on its central pixel effectively and enhance the robustness to noise. Experiments on images with different noisy levels demonstrate that the proposed algorithm is effective and more robust to noise than standard FCM and some other extended FCM algorithms.

关键词： Image segmentation Fuzzy c-means spatial information Anti-noise

来源： cnki会议评论

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Data Science and Informetrics 2023年第2期3卷 79-90页

作者： Guohu Lin Hangzhou Dianzi University School of Foreign StudiesHangzhouChina

The spatial information of literature refers to the representation of physical or conscious space in literary works,including position,shape,structure,features,and *** spatial information organization and its method are essential to the whole process of literature production,circulation,acceptance,and reproduction,which is conducive to a deeper exploration of the aesthetic essence of literature in the information *** the organization of spatial information in science fiction as an example,this paper investigates the way of interaction between informatics and literature,explores the function of spatial information in the narrative of science fiction,and discovers digital humanistic laws of literary information *** study finds that the spatial information of early science fiction is organized in horizontal,vertical,axial,and causal modes;in the era of digital humanities,influenced by information technology such as the internet,virtual reality,and artificial intelligence,literary space has experienced revolutions characteristic of time-space integration,boundary dissolution,dimensional change,and virtualization;the spatial information organization of contemporary science fiction adopts nested,reticulated,parallel,interactive,and reverse patterns;on the whole,it is featured with fluidity,chaos,correlation,and mutation,creating a unique digital humanistic spectacle.

关键词： Digital humanities Science fiction spatial information Organization patterns Organization features

Selective sampling with Gromov–Hausdorff metric:Efficient dense-shape correspondence via Confidence-based sample consensus

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虚拟现实与智能硬件（中英文） 2024年第1期6卷 30-42页

作者： Dvir GINZBURG Dan RAVIV Department of Engineering University of Tel AvivIsrael

Background Functional mapping, despite its proven efficiency, suffers from a “chicken or egg” scenario, in that, poor spatial features lead to inadequate spectral alignment and vice versa during training, often resulting in slow convergence, high computational costs, and learning failures, particularly when small datasets are used. Methods A novel method is presented for dense-shape correspondence, whereby the spatial information transformed by neural networks is combined with the projections onto spectral maps to overcome the “chicken or egg” challenge by selectively sampling only points with high confidence in their alignment. These points then contribute to the alignment and spectral loss terms, boosting training, and accelerating convergence by a factor of five. To ensure full unsupervised learning, the Gromov–Hausdorff distance metric was used to select the points with the maximal alignment score displaying most confidence. Results The effectiveness of the proposed approach was demonstrated on several benchmark datasets, whereby results were reported as superior to those of spectral and spatial-based methods. Conclusions The proposed method provides a promising new approach to dense-shape correspondence, addressing the key challenges in the field and offering significant advantages over the current methods, including faster convergence, improved accuracy, and reduced computational costs.

关键词： Dense-shape correspondence spatial information Neural networks Spectral maps Selective sampling

Improved evidential fuzzy c-means method

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Journal of Systems Engineering and Electronics 2018年第1期29卷 187-195页

作者： JIANG Wen YANG Tian SHOU Yehang TANG Yongchuan HU Weiwei School of Electronics and information Northwestern Polytechnical University

Dempster-Shafer evidence theory(DS theory) is widely used in brain magnetic resonance imaging(MRI) segmentation,due to its efficient combination of the evidence from different sources. In this paper, an improved MRI segmentation method,which is based on fuzzy c-means(FCM) and DS theory, is proposed. Firstly, the average fusion method is used to reduce the uncertainty and the conflict information in the pictures. Then, the neighborhood information and the different influences of spatial location of neighborhood pixels are taken into consideration to handle the spatial information. Finally, the segmentation and the sensor data fusion are achieved by using the DS theory. The simulated images and the MRI images illustrate that our proposed method is more effective in image segmentation.

关键词： average fusion spatial information Dempster-Shafer evidence theory(DS theory) fuzzy c-means(FCM) magnetic resonance imaging(MRI) image segmentation

Multi-spectral remote sensing image enhancement method based on PCA and IHS transformations

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2011年第6期12卷 453-460页

作者： Shan-long LU Le-jun ZOU Xiao-hua SHEN Wen-yuan WU Wei ZHANG Department of Earth Sciences Zhejiang University Hangzhou 310027 China Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China China A ero Geophysical Survey & Remote Sensing Center for Land and Resources Beijing 100083 China

This paper introduces a new enhancement method for multi-spectral satellite remote sensing imagery,based on principal component analysis(PCA) and intensity-hue-saturation(IHS) *** PCA and the IHS transformations are used to separate the spatial information of the multi-spectral image into the first principal component and the intensity component,*** enhanced image is obtained by replacing the intensity component of the IHS transformation with the first principal component of the PCA transformation,and undertaking the inverse IHS *** objective of the proposed method is to make greater use of the spatial and spectral information contained in the original multi-spectral *** the basis of the visual and statistical analysis results of the experimental study,we can conclude that the proposed method is an ideal new way for multi-spectral image quality enhancement with little color *** has potential advantages in image mapping optimization,object recognition,and weak information sharpening.

关键词： Remote sensing Principal component analysis(PCA) Intensity-hue-saturation(IHS) transformation Image enhancement spatial information Spectral information

spatial data trusts:an emerging governance framework for sharing spatial data

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International Journal of Digital Earth 2023年第1期16卷 1607-1639页

作者： Nenad Radosevic Matt Duckham Mohammad Saiedur Rahaman Serene Ho Katherine Williams Tanzima Hashem Yaguang Tao School of Science RMIT UniversityMelbourneAustralia School of Computing Technologies RMIT UniversityMelbourneAustralia Frontier SI MelbourneAustralia Department of Computer Science and Engineering Bangladesh University of Engineering and TechnologyDhakaBangladesh

Data Trusts are an important emerging approach to enabling the much wider sharing of data from many different sources and for many different purposes,backed by the confidence of clear and unambiguous data *** Trusts combine the technical infrastructure for sharing data with the governance framework of a legal *** concept of a data Trust applied specifically to spatial data offers significant opportunities for new and future applications,addressing some longstanding barriers to data sharing,such as location privacy and data *** paper introduces and explores the concept of a‘spatial data Trust’by identifying and explaining the key functions and characteristics required to underpin a data Trust for spatial *** work identifiesfive key features of spatial data Trusts that demand specific attention and connects these features to a history of relevant work in thefield,including spatial data infrastructures(SDIs),location privacy,and spatial data *** conclusions identify several key strands of research for the future development of this rapidly emerging framework for spatial data sharing.

关键词： Data governance spatial information location privacy indigenous data sovereignty spatial data quality

The application of China’s land observation satellites within the framework of Digital Earth and its key technologies

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International Journal of Digital Earth 2012年第3期5卷 189-201页

作者： Wen Xu China Centre for Resources Satellite Data and Application Haidian DistrictBeijingChina

Digital Earth is an interdisciplinary field involving space technology,information technology,and *** article introduces the land observation satellite system of China and discusses the requirements for satellite payloads in terms of spatial,temporal,and spectral resolution to establish a Digital *** applications of land satellites under the framework of Digital Earth are introduced from the perspectives of data support,special subject services,and integrated information *** is concluded that China’s land observation satellites and ground processing systems will be fundamental components of the Digital Earth system,in which satellite data and their derived information will serve as the principal information source and greatly promote applications of Digital Earth.

关键词： land satellite Digital Earth spatial information spatial data infrastructure Earth observation

Solution of Multiple-Point Statistics to Extracting information from Remotely Sensed Imagery

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Journal of China University of Geosciences 2008年第4期19卷 421-428页

作者：葛咏白鹤翔成秋明 State Key Laboratory of Resources and Environmental information System Institute of Geographic Sciences & Natural Resources Research Chinese Academy of Sciences Department of Earth and Space Science and Engineering York University State Key Laboratory of Geological Processes and Mineral Resources China University of Geosciences

Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information. Therefore, there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery. In the current article, a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification. The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese Yellow River delta on August 8, 1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier （MLC）.

关键词： information extraction spectral information spatial information multiple-point statistics

spatial REGULARIZATION OF CANONICAL CORRELATION ANALYSIS FOR LOW-RESOLUTION FACE RECOGNITION

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Transactions of Nanjing University of Aeronautics and Astronautics 2013年第1期30卷 77-81页

作者：周旭东陈晓红钱强 College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics information Engineering College Yangzhou University College of Science Nanjing University of Aeronautics and Astronautics

Canonical correlation analysis ( CCA ) based methods for low-resolution ( LR ) face recognition involve face images with different resolutions ( or multi-resolutions ), *** and high-resolution ( HR ) .For single-resolution face recognition , researchers have shown that utilizing spatial information is beneficial to improving the recognition accuracy , mainly because the pixels of each face are not independent but spatially *** , for a multi-resolution scenario , there are no related *** , a method named spatial regularization of canonical correlation analysis ( SRCCA ) is developed for LR face recognition to improve the performance of CCA by the regularization utilizing spatial information of different resolution *** , the impact of LR and HR spatial regularization terms on LR face recognition is analyzed through experiments.

关键词： face recognition canonical correlation analysis low-resolution spatial information