Image fusion

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In computer vision, Multisensor Image fusion is the process of combining relevant information from two or more images into a single image. The resulting image will be more informative than any of the input images. (Wikipedia.org)






Conferences related to Image fusion

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2020 IEEE 23rd International Conference on Information Fusion (FUSION)

The International Conference on Information Fusion is the premier forum for interchange of the latest research in data and information fusion, and its impacts on our society. The conference brings together researchers and practitioners from academia and industry to report on the latest scientific and technical advances.


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


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Periodicals related to Image fusion

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


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Most published Xplore authors for Image fusion

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Xplore Articles related to Image fusion

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Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012

Comparison of image processing techniques is critically important in deciding which algorithm, method, or metric to use for enhanced image assessment. Image fusion is a popular choice for various image enhancement applications such as overlay of two image products, refinement of image resolutions for alignment, and image combination for feature extraction and target recognition. Since image fusion is used in ...


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2019 China-Qatar International Workshop on Artificial Intelligence and Applications to Intelligent Manufacturing (AIAIM), 2019

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A novel visible image fusion algorithm based on downsampling fractional wavelet transform and shearlet transform

2016 International Conference on Communication and Electronics Systems (ICCES), 2016

Due to the disadvantage of traditional Shearlet transform fusion method, namely, Shearlet transform may emerge Gibbs phenomenon and exist large-scale image data, and in order to suppress such pseudo-Gibbs effect in the process of downsampling, we propose a novel method based on downsampling fractional wavelet transform and Shearlet transform. Our proposed method combines the theory of compressed sensing with decomposition ...


SAR/IR sensor image fusion and real-time implementation

Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers, 1995

This paper presents a real time SAR/IR fusion system for automatic target recognition (ATR) applications. The system contains three major components: preprocessing, registration and fusion. The registration algorithm is based on Zheng-Chellappa's (see IEEE Transactions on Image Processing, no.7, p.311, 1993) APFBR work. The fusion algorithm employs a biologically inspired merging rule to carry out SAR/IR fusion at the pixel ...


Strip steel surface defect image mosaic method based on area CCD

The 2nd International Conference on Information Science and Engineering, 2010

The strip steel surface defects which collected by area CCD are not continuous image, there are overlap between each other. In order to join the overlapped images properly, and meantime maintain the original image feature, a weighted average fusion method based on provincial characteristics is adapted. A linear interpolation image fusion method is proposed for improving the contrast of the ...


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Educational Resources on Image fusion

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IEEE.tv Videos

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Robotics History: Narratives and Networks Oral Histories: Ray Jarvis
Robotics History: Narratives and Networks Oral Histories: Minoru Asada
Resistive Coupled VO2 Oscillators for Image Recognition - Elisabetta Corti - ICRC 2018
Fog Computing Manageability and Orchestration: How To Fuse Cloud, Network, and Fog - Marcelo Yannuzzi, Fog World Congress 2017

IEEE-USA E-Books

  • Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study

    Comparison of image processing techniques is critically important in deciding which algorithm, method, or metric to use for enhanced image assessment. Image fusion is a popular choice for various image enhancement applications such as overlay of two image products, refinement of image resolutions for alignment, and image combination for feature extraction and target recognition. Since image fusion is used in many geospatial and night vision applications, it is important to understand these techniques and provide a comparative study of the methods. In this paper, we conduct a comparative study on 12 selected image fusion metrics over six multiresolution image fusion algorithms for two different fusion schemes and input images with distortion. The analysis can be applied to different image combination algorithms, image processing methods, and over a different choice of metrics that are of use to an image processing expert. The paper relates the results to an image quality measurement based on power spectrum and correlation analysis and serves as a summary of many contemporary techniques for objective assessment of image fusion algorithms.

  • Table of Contents

    Table of Contents

  • A novel visible image fusion algorithm based on downsampling fractional wavelet transform and shearlet transform

    Due to the disadvantage of traditional Shearlet transform fusion method, namely, Shearlet transform may emerge Gibbs phenomenon and exist large-scale image data, and in order to suppress such pseudo-Gibbs effect in the process of downsampling, we propose a novel method based on downsampling fractional wavelet transform and Shearlet transform. Our proposed method combines the theory of compressed sensing with decomposition of the different gray distribution feature source images. In our paper, the comparison experimental results are conducted respectively by using image fusion rules of regional maximum value and variance matching. The results show that our method can avoid the pseudo-Gibbs phenomenon, compared with traditional method, our method reduces the amount of data transmission and fusion, enhancing the fusion efficiency, and also shortens the image fusion time to no more than 50s.

  • SAR/IR sensor image fusion and real-time implementation

    This paper presents a real time SAR/IR fusion system for automatic target recognition (ATR) applications. The system contains three major components: preprocessing, registration and fusion. The registration algorithm is based on Zheng-Chellappa's (see IEEE Transactions on Image Processing, no.7, p.311, 1993) APFBR work. The fusion algorithm employs a biologically inspired merging rule to carry out SAR/IR fusion at the pixel level. In the fused images, features from individual sensor images are not only preserved but also enhanced. The fused images are more suitable for visual perception and ATR operations. The system has been implemented on a SIMD parallel processor to achieve real-time performance. It has been extensively tested on real SAR/IR data.

  • Strip steel surface defect image mosaic method based on area CCD

    The strip steel surface defects which collected by area CCD are not continuous image, there are overlap between each other. In order to join the overlapped images properly, and meantime maintain the original image feature, a weighted average fusion method based on provincial characteristics is adapted. A linear interpolation image fusion method is proposed for improving the contrast of the fused image, enhance the high frequency information, and eliminate matching trace. With linear interpolation image fusion, the pixels gray value of overlap area is replaced by the corresponding weighted average of gray value in two images. Experimental results show that the fusion method can meet the requirements of strip steel defect detection. And it can effectively eliminate the traces of image mosaic, make the image clearer. This made a foundation for the strip surface defect identification and quality evaluation.

  • Research on image fusion for visible and infrared images

    According to study on the definition of information fusion and the analysis about the nature of image fusion, the image fusion method is divided into spatial domain and frequency domain. By analyzing and comparing the performance of the both two, the advantages and prospects of the latter are confirmed. In frequency domain, the fusion method based on two-dimensional discrete wavelet transform is mainly introduced. Based on high and low filters, it decomposes the source image into couples of sub-band images which highlight image's detail information in different spatial resolutions. By means of applying different fusion rules to distinct sub-band images, the final fused image is achieved by using the inverse discrete wavelet transform. The experimental results indicate that the fused image successfully reflects the comprehensive information on the target object or the target scene.

  • Finger print fusion using Daubechies (Db1) wavelet transformation and quality measures

    Image Fusion is mechanism that is used to associate admissible information from a set of images of same scene into a single image. A Fused image is more informative, clear, noise free. In this paper Finger prints are used as input to image fusion mechanism. Daubechies Wavelet transformation is applied on them. Various fusion rules are applied on wavelet coefficients like mean, add, maximum, minimum. Quality of fingerprints are being tested using parameters are PSNR, Average Difference, Entropy, Chi-Square.

  • New transform techniques for enhancement and fusion of multispectral and hyperspectral images

    This paper presents a new approach to the development of multispectral/hyperspectral image enhancement and fusion algorithms. In approaches used up to now for image enhancement, the bands are typically processed separately, and this results in considerable distortion. The amount of information in many bands are also not very efficiently used. The objective of this work is to utilize the amount of information available more effectively, remove such distortions and to improve the appearance of the images. To realize this goal, we developed two new algorithms using transform techniques. In the resulting algorithms developed, image enhancement and image fusion are considered together

  • A novel approach for fusing LIDAR and visual camera images in unstructured environment

    Image fusion is the process of merging all similar information from two or more images into a single image. The aim is to provide an image fusion method for fusing the images from the different modalities so that the fusion image will give more information without losing input information and also without any redundancy. This paper gives the efficient method for fusion purpose, by fusing LIDAR and visual camera images. The objective of this proposed method is to develop an image fusion algorithm and its applications in automated navigation in an unstructured environment.

  • Design of a simple ultrasound/CT fusion image fusion solution for the evaluation of prostate seed brachytherapy

    The purpose of this project is to devise a solution that will enable physicians, medical physicists and dosimetrists to quantitatively evaluate the success of prostate brachytherapy procedures. It is proposed that a simple ultrasound/CT image fusion solution can be developed and implemented to improve the current post-surgical evaluation process.



Standards related to Image fusion

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No standards are currently tagged "Image fusion"


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