2,570 resources related to Image fusion
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The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.
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.
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
All fields of satellite, airborne and ground remote sensing.
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.
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.
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 ...
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.
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-- ...
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 ...
2019 China-Qatar International Workshop on Artificial Intelligence and Applications to Intelligent Manufacturing (AIAIM), 2019
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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 ...
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 ...
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 ...
P2020 Establishing Image Quality Standards for Automotive
Programming Human Ethics: Cui Bono? - IEEE AI & Ethics Summit 2016
Hamid R Tizhoosh - Fuzzy Image Processing
Solving Sparse Representation for Image Classification using Quantum D-Wave 2X Machine - IEEE Rebooting Computing 2017
Zohara Cohen AMA EMBS Individualized Health
Skillful Manipulation Based on High-Speed Sensory-Motor Fusion
Broadband IQ, Image Reject, and Single Sideband Mixers: MicroApps 2015 - Marki Microwave
IEEE Low-Power Image Recognition Challenge (LPIRC)
Technology for Health Summit 2017 - Panel II: Managing the data deluge linked to connected technology in health
Q&A with Ryan Dailey: IEEE Rebooting Computing Podcast, Episode 12
Tapping the Computing Power of the Unconscious Brain
CPIQ Update and the Case for Image Quality Standards in Automotive
Welcome: Low Power Image Recognition Challenge
Low Power Image Recognition: The Challenge Continues
My Computer Speaks Colors! Fuzzy Color Spaces for Image Understanding, Description and Retrieval
Robotics History: Narratives and Networks Oral Histories: Ray Jarvis
Robotics History: Narratives and Networks Oral Histories: Minoru Asada
Mengjie Zhang: Evolutionary Deep Learning for Image Analysis
Deeper Neural Networks - Kurt Keutzer - LPIRC 2019
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.
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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.
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.
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.
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.
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.
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
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.
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.
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