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Novel Cooperative Neural Fusion Algorithms for Image Restoration and Image Fusion
IEEE Transactions on Image Processing, 2007To deal with the problem of restoring degraded images with non-Gaussian noise, this paper proposes a novel cooperative neural fusion regularization (CNFR) algorithm for image restoration. Compared with conventional regularization algorithms for image restoration, the proposed CNFR algorithm can relax need of the optimal regularization parameter to be ...
Youshen, Xia, Mohamed S, Kamel
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Image fusion with IKONOS images
SPIE Proceedings, 2003The techniques for fusion of satellite images with different spatial resolutions aims to enhance the image quality, that allows a better visual interpretation. Ideally, the resulting image must keep the spectral resolution, leading to a more precise image segmentation and classification. Many different methods have been proposed to perform image fusion
Mario J. Schneider +2 more
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Image registration & image fusion
Proceedings of the International Conference and Workshop on Emerging Trends in Technology, 2010This paper aims to present Image registration and Image fusion used for Image processing. Sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system ...
Shuneza Sayed, Smita Jangale
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Proceedings., International Conference on Image Processing, 2002
Presents a method to make dynamic image analysis by image fusion. This method is unsupervised and does not require previous knowledge of the number of relevant parameters as in statistical methods. It uses set operations to segment recursively a given region if at any following time this region appears not to be homogeneous.
Y. Hode +3 more
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Presents a method to make dynamic image analysis by image fusion. This method is unsupervised and does not require previous knowledge of the number of relevant parameters as in statistical methods. It uses set operations to segment recursively a given region if at any following time this region appears not to be homogeneous.
Y. Hode +3 more
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Multimodal Imaging and Image Fusion
2017In multimodal imaging diverse imaging techniques are applied to the same subject usually within a limited time frame in order to capture the same functional, morphologic, and metabolic state of the subject. The historical most compelling need for multimodal imaging stems from the requirement to match functional or metabolic information captured with, e.
Wehrl, H., Amend, M., Thielcke, A.
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2021
Image information fusion is an information technology and process that comprehensively processes information data from multiple image sensors to obtain more comprehensive, accurate, and reliable results than using only single sensor information data (Theodoridis and Koutroumbas 2003; Zhang 2015f).
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Image information fusion is an information technology and process that comprehensively processes information data from multiple image sensors to obtain more comprehensive, accurate, and reliable results than using only single sensor information data (Theodoridis and Koutroumbas 2003; Zhang 2015f).
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2013
Medical imaging consists of a wide range of modalities, each with its respective advantages and limitations. Image fusion technologies may allow the advantage of one imaging modality to overcome the limitations of another. In this chapter, the current state of hardware and software fusion technologies is discussed.
Gerd Brunner +4 more
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Medical imaging consists of a wide range of modalities, each with its respective advantages and limitations. Image fusion technologies may allow the advantage of one imaging modality to overcome the limitations of another. In this chapter, the current state of hardware and software fusion technologies is discussed.
Gerd Brunner +4 more
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Machine Vision and Applications, 1990
A hierarchical image fusion scheme is presented that preserves those details from the input images that are most relevant to visual perception. Results show that fused images present a more detailed representation of the scene and provide information that cannot be obtained by viewing the input images separately.
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A hierarchical image fusion scheme is presented that preserves those details from the input images that are most relevant to visual perception. Results show that fused images present a more detailed representation of the scene and provide information that cannot be obtained by viewing the input images separately.
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2018
Image fusion at the pixel level can be implemented as simply as an arithmetic average; however, there are many techniques that improve on the simple methods. For example, a weighted sum of two or more input images is a valid image fusion. Principal component analysis (PCA) can be applied to decide the weights of input images (i.e., which input is more ...
Zheng Liu, Yufeng Zheng, Erik Blasch
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Image fusion at the pixel level can be implemented as simply as an arithmetic average; however, there are many techniques that improve on the simple methods. For example, a weighted sum of two or more input images is a valid image fusion. Principal component analysis (PCA) can be applied to decide the weights of input images (i.e., which input is more ...
Zheng Liu, Yufeng Zheng, Erik Blasch
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2018
An image fusion process should preserve all useful patterns from the source images while minimizing artifacts that could interfere with subsequent analyses or distract human observers. Given that it is nearly impossible to fuse images without introducing some form of distortion, measurements are necessary to present a fused image quality (IQ) for user ...
Zheng Liu, Yufeng Zheng, Erik Blasch
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An image fusion process should preserve all useful patterns from the source images while minimizing artifacts that could interfere with subsequent analyses or distract human observers. Given that it is nearly impossible to fuse images without introducing some form of distortion, measurements are necessary to present a fused image quality (IQ) for user ...
Zheng Liu, Yufeng Zheng, Erik Blasch
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