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Moment-Based Dense Correspondence Matching Robust to Image Variation
2017 IEEE International Symposium on Multimedia (ISM), 2017SIFT flow adopts SIFT descriptor to find correspondence between two images. However, SIFT flow is not robust to scale and rotation for dense corresponding matching. In this paper, we propose moment-based dense correspondence matching which is robust to image variation. First, we apply Zernike moments to SIFT descriptor, i.e. Moments of Gradients (MoG).
Inyong Yun +3 more
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Novel dense matching algorithm with Voronoi decomposition of images
Optical Engineering, 2005A novel dense stereo matching algorithm based on propagation within a Voronoi decomposition of the image plane is proposed. A weighted sum of squared differences is developed as the cost function. The size of the window is adaptive; it is set in inverse proportion to the texture density inside it for reliable propagation.
Li Tang, Chengke Wu, Hung Tat Tsui
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Real-time dense stereo matching architecture for high-resolution image
2015 International SoC Design Conference (ISOCC), 2015In this paper we propose a real-time dense stereo matching architecture for a high-resolution image. Stereo matching shows the best performance to detect objects and to estimate distance detection. So, many algorithms have been developed, such as local matching and global matching.
Seonyoung Lee +2 more
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Stereo Image Dense Matching Based on SGM Constrained by Feature Matching
2023 9th International Conference on Computer and Communications (ICCC), 2023Tao Ma +5 more
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Through-Water Dense Image Matching for Shallow Water Bathymetry
Photogrammetric Engineering & Remote Sensing, 2019The introduction of Dense Image Matching (DIM) has reactivated the interest in photogrammetric surface mapping, as it allows the derivation of Digital Elevation Models with a spatial resolution in the range of the ground sampling distance of the aerial images.
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Scale Selection in SIFT Flow for Robust Dense Image Matching
2013SIFT flow is a method to align an image to its neighbors in a large image collection consisting of a variety of scenes. Originally proposed for cross-scene alignment, it has good potential for robust dense matching between images of a scene taken under large viewing condition changes.
Shimiao Li, Wei Xiong
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Cross-modal semi-dense image matching
In this thesis, we introduce a novel deep learning-based image matching method for cross-modal, cross-view local feature matching between thermal infrared (TIR) and visible-band images. Unlike visible-band images, TIR images are less susceptible to adverse lighting and weather conditions but present difficulties in matching due to significant texture ...openaire +1 more source
Automated molecular-image cytometry and analysis in modern oncology
Nature Reviews Materials, 2020Ralph Weissleder, Hakho Lee
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nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Nature Methods, 2020Fabian Isensee +2 more
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