• 제목/요약/키워드: Multi-source Image Fusion

검색결과 12건 처리시간 0.038초

Development and Implementation of Multi-source Remote Sensing Imagery Fusion Based on PCI Geomatica

  • Yu, ZENG;Jixian, ZHANG;Qin, YAN;Pinglin, QIAO
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1334-1336
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    • 2003
  • On the basis of comprehensive analysis and summarization of the image fusion algorithms provided by PCI Geomatica software, deficiencies in image fusion processing functions of this software are put forwarded in this paper. This limitation could be improved by further developing PCI Geomatica on the user’ side. Five effective algorithms could be added into PCI Geomatica. In this paper, the detailed description of how to customize and further develop PCI Geomatica by using Microsoft Visual C++ 6.0, PCI SDK Kit and GDB technique is also given. Through this way, the remote sensing imagery fusion functions of PCI Geomatica software can be extended.

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PATN: Polarized Attention based Transformer Network for Multi-focus image fusion

  • Pan Wu;Zhen Hua;Jinjiang Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권4호
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    • pp.1234-1257
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    • 2023
  • In this paper, we propose a framework for multi-focus image fusion called PATN. In our approach, by aggregating deep features extracted based on the U-type Transformer mechanism and shallow features extracted using the PSA module, we make PATN feed both long-range image texture information and focus on local detail information of the image. Meanwhile, the edge-preserving information value of the fused image is enhanced using a dense residual block containing the Sobel gradient operator, and three loss functions are introduced to retain more source image texture information. PATN is compared with 17 more advanced MFIF methods on three datasets to verify the effectiveness and robustness of PATN.

AUTOMATIC BUILDING EXTRACTION BASED ON MULTI-SOURCE DATA FUSION

  • Lu, Yi Hui;Trinder, John
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.248-250
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    • 2003
  • An automatic approach and strategy for extracting building information from aerial images using combined image analysis and interpretation techniques is described in this paper. A dense DSM is obtained by stereo image matching. Multi-band classification, DSM, texture segmentation and Normalised Difference Vegetation Index (NDVI) are used to reveal building interest areas. Then, based on the derived approximate building areas, a shape modelling algorithm based on the level set formulation of curve and surface motion has been used to precisely delineate the building boundaries. Data fusion, based on the Dempster-Shafer technique, is used to interpret simultaneously knowledge from several data sources of the same region, to find the intersection of propositions on extracted information derived from several datasets, together with their associated probabilities. A number of test areas, which include buildings with different sizes, shape and roof colour have been investigated. The tests are encouraging and demonstrate that the system is effective for building extraction, and the determination of more accurate elevations of the terrain surface.

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재능 유전인자를 갖는 네스티드 유전자 알고리듬을 이용한 새로운 다중 초점 이미지 융합 기법 (A Novel Multi-focus Image Fusion Scheme using Nested Genetic Algorithms with "Gifted Genes")

  • 박대철;론넬 아톨레
    • 한국인터넷방송통신학회논문지
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    • 제9권1호
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    • pp.75-87
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    • 2009
  • 본 논문에서 이미지 선명도 함수의 최적화에 의해 융합 법칙이 유도되는 새로운 이미지 융합 접근법을 제안한다. 선명도 함수에 비교하여 소스 이미지로부터 최적 블록을 통계적으로 선택하기 위하여 유전자 알고리듬이 사용되었다. 변이 연산에 의해 만들어진 유전인자들의 포격을 통해서 찾아진 재능 유전 인자를 갖는 새로운 네스티드 유전자 알고리듬을 설계하였고 구현하였다. 알고리듬의 수렴은 해석적으로, 실험적으로 그리고 통계적으로 3개의 테스트 함수를 사용하여 표준 GA와 비교하였다. 결과의 GA는 변수와 집단 크기에 불변이며, 최소 20 개체이면 시험에 충분하다는 것을 알 수 있었다. 융합 응용에서 모집단내의 각 개체는 입력 블록을 나타내는 유한한 이산 값을 갖는 개체이다. 이미지 융합 실험에 제안한 기법의 성능은 출력 품질 척도로 상호 정보량(MI)으로 특징지워진다. 제안한 방법은 C=2 입력 이미지에 대해 테스트되었다. 제안한 방법의 실험 결과는 현재의 다중 초점 이미지 융합 기법에 대한 실제적이고 매력적인 대안이 됨을 보여준다.

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Image Fusion for Improving Classification

  • Lee, Dong-Cheon;Kim, Jeong-Woo;Kwon, Jay-Hyoun;Kim, Chung;Park, Ki-Surk
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1464-1466
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    • 2003
  • classification of the satellite images provides information about land cover and/or land use. Quality of the classification result depends mainly on the spatial and spectral resolutions of the images. In this study, image fusion in terms of resolution merging, and band integration with multi-source of the satellite images; Landsat ETM+ and Ikonos were carried out to improve classification. Resolution merging and band integration could generate imagery of high resolution with more spectral bands. Precise image co-registration is required to remove geometric distortion between different sources of images. Combination of unsupervised and supervised classification of the fused imagery was implemented to improve classification. 3D display of the results was possible by combining DEM with the classification result so that interpretability could be improved.

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Classifier Combination Based Source Identification for Cell Phone Images

  • Wang, Bo;Tan, Yue;Zhao, Meijuan;Guo, Yanqing;Kong, Xiangwei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권12호
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    • pp.5087-5102
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    • 2015
  • Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

DCNN Optimization Using Multi-Resolution Image Fusion

  • Alshehri, Abdullah A.;Lutz, Adam;Ezekiel, Soundararajan;Pearlstein, Larry;Conlen, John
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권11호
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    • pp.4290-4309
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    • 2020
  • In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

Development of a multi-modal imaging system for single-gamma and fluorescence fusion images

  • Young Been Han;Seong Jong Hong;Ho-Young Lee;Seong Hyun Song
    • Nuclear Engineering and Technology
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    • 제55권10호
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    • pp.3844-3853
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    • 2023
  • Although radiation and chemotherapy methods for cancer therapy have advanced significantly, surgical resection is still recommended for most cancers. Therefore, intraoperative imaging studies have emerged as a surgical tool for identifying tumor margins. Intraoperative imaging has been examined using conventional imaging devices, such as optical near-infrared probes, gamma probes, and ultrasound devices. However, each modality has its limitations, such as depth penetration and spatial resolution. To overcome these limitations, hybrid imaging modalities and tracer studies are being developed. In a previous study, a multi-modal laparoscope with silicon photo-multiplier (SiPM)-based gamma detection acquired a 1 s interval gamma image. However, improvements in the near-infrared fluorophore (NIRF) signal intensity and gamma image central defects are needed to further evaluate the usefulness of multi-modal systems. In this study, an attempt was made to change the NIRF image acquisition method and the SiPM-based gamma detector to improve the source detection ability and reduce the image acquisition time. The performance of the multi-modal system using a complementary metal oxide semiconductor and modified SiPM gamma detector was evaluated in a phantom test. In future studies, a multi-modal system will be further optimized for pilot preclinical studies.

Big Data Architecture Design for the Development of Hyper Live Map (HLM)

  • Moon, Sujung;Pyeon, Muwook;Bae, Sangwon;Lee, Dorim;Han, Sangwon
    • 한국측량학회지
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    • 제34권2호
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    • pp.207-215
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    • 2016
  • The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

웹 처리 서비스(WPS) 표준의 위성영상 정보처리 시험 적용 (Testing Application of Web Processing Service (WPS) Standard to Satellite Image Processing)

  • 윤구선;이기원
    • 대한원격탐사학회지
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    • 제31권3호
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    • pp.245-253
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    • 2015
  • 위성 영상정보의 민간 활용이 확대되면서 원격 서버에서 다중 위성 영상정보의 상호 운영과 융합처리 서비스에 대한 실제적인 필요성이 증가하고 있다. 이러한 추세에 따라 위성 영상정보에서 얻어지는 파생 정보를 위한 OGC 표준의 중요성이 강조되고 있다. 이번 연구에서는 GeoServer와 OTB와 같은 오픈소스를 기반으로 하여 WPS 표준에 대한 시험 구현을 통하여 위성정보 처리 분야에서 이러한 표준의 적용 가능성을 예시하고자 하였다. WPS 표준은 단독으로 적용될 수도 있으나 위성영상 정보처리를 포함하는 공간정보 웹 포털은 WMS, WFS, WCS와 WMTS 뿐만 아니라 카탈로그 서비스 표준 등의 요소를 같이 고려해야 한다. 앞으로 이러한 공간정보 국제표준 사양은 보다 많은 실무 적용 사례의 구축과 지속적인 관련 기술 개발을 통하여 실무적인 분석처리 기능을 제공하는 위성영상 정보시스템의 기관 간 상호운영이나 정보 콘텐츠의 효과적인 유통 체계 구축을 위한 중요한 접근 방식이 될 것으로 기대한다.