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A robust deformed image matching method for multi-source image matching
Infrared Physics & Technology, 2021Abstract Multi-source image matching is a challenging task due to the presence of image distortion, as well as significant intensity changes between image pairs in corresponding regions. In addition, the influences of variant scales and multiplicative noises will also have an adverse effect on the matching accuracy.
Guili Xu +5 more
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Matching Images Using Linear Features
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984We describe techniques for matching two images or an image and a map. This operation is basic for machine vision and is needed for the tasks of object recognition, change detection, map up-dating, passive navigation, and other tasks. Our system uses line-based descriptions, and matching is accomplished by a relaxation operation which computes most ...
G, Medioni, R, Nevatia
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SPIE Proceedings, 1985
During the past decade, three major categories of image matching algorithms have emerged: Signal-processing-based, artificial-intelligence-based, and a combination of these methods called hybrid techniques. This paper summarizes some of these techniques and their potential in remote sensing applications.
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During the past decade, three major categories of image matching algorithms have emerged: Signal-processing-based, artificial-intelligence-based, and a combination of these methods called hybrid techniques. This paper summarizes some of these techniques and their potential in remote sensing applications.
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2001
After the rendering phase is complete, two images are available: the sensor image and the predicted image. The matching phase of Render-Match-Refine (RMR) is formulated in terms of the difference in pixel values between these two images. This difference or error indicates the quality of the set of scene parameters used to render the prediction.
Mark R. Stevens, J. Ross Beveridge
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After the rendering phase is complete, two images are available: the sensor image and the predicted image. The matching phase of Render-Match-Refine (RMR) is formulated in terms of the difference in pixel values between these two images. This difference or error indicates the quality of the set of scene parameters used to render the prediction.
Mark R. Stevens, J. Ross Beveridge
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Matching 2D Gel Electrophoresis Images
Journal of Chemical Information and Computer Sciences, 2003Automatic alignment (matching) of two-dimensional gel electrophoresis images is of primary interest in the field of proteomics. The proposed method of 2D gel image matching is based on fuzzy alignment of features, extracted from gels' images, and it allows both global and local interpolation of image grid, followed by brightness interpolation.
K, Kaczmarek +3 more
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Aligned matching: An efficient image matching technique
2009 16th IEEE International Conference on Image Processing (ICIP), 2009Local feature based methods have achieved a great success in the field of image matching due to its invariance under typical image transformations. However, local features are often not invariant under complex non-affine transformations, which makes the matching methods ineffective.
null Yang Duanduan, Andrzej Sluzek
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Compressed Pattern Matching in JPEG Images
Data Compression Conference, 2005The possibility of applying compressed matching in JPEG encoded images is investigated and the problems raised by the scheme are discussed. A part of the problems can be solved by the use of some auxiliary data which yields various time/space trade-offs. Finally, approaches to deal with extensions such as allowing scaling or rotations are suggested.
Klein, Shmuel T., Shapira, Dana
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Best-match retrieval for structured images
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001Propose a methodology for fast best-match retrieval of structured images. A triangle inequality property for the tree-distance introduced by Oflazer (1997) is proven. This property is, in turn, applied to obtain a saturation algorithm of the trie used to store the database of the collection of pictures.
FERRO, Alfredo +3 more
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Tampered Image Detection Using Image Matching
2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation, 2008With the development of image processing software, such as Photoshop, scientific analysis for detecting tampered images becomes a critical research issue. A hybrid image matching algorithm for image analysis is proposed and evaluated. Features are extracted using blob detectors and interest point detectors.
Zhenghao Li +3 more
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Image Classification by Image Matching
2001Image classification is usually performed by making measurements on the image itself. For example, texture measurements are made to classify an image as “natural” or “urban.” This chapter describes an experiment that we carried out to determine whether an image could be classified by matching the image against databases of images, where each database ...
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