Cross-Modality Image Matching Network With Modality-Invariant Feature Representation for Airborne-Ground Thermal Infrared and Visible Datasets
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3099506
Abstract: Thermal infrared (TIR) remote-sensing imagery can allow objects to be imaged clearly at night through the long-wave infrared, so that the fusion of thermal infrared and visible (VIS) imagery is a way to improve the… read more here.
Keywords: modality invariant; invariant feature; cross modality; feature representation ... See more keywords
R₂FD₂: Fast and Robust Matching of Multimodal Remote Sensing Images via Repeatable Feature Detector and Rotation-Invariant Feature Descriptor
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3264610
Abstract: Identifying feature correspondences between multimodal images is facing enormous challenges because of the significant differences both in radiation and geometry. To address these problems, we propose a novel feature matching method (named R2FD2) that is… read more here.
Keywords: invariant feature; rotation invariant; feature; feature detector ... See more keywords
A Grassmannian Graph Approach to Affine Invariant Feature Matching
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2019.2959722
Abstract: In this work, we present a novel, theoretical approach to address one of the longstanding problems in computer vision: 2D and 3D affine invariant feature matching. Our proposed Grassmannian Graph (GrassGraph) framework employs a two… read more here.
Keywords: grassmannian graph; feature; invariant feature; affine invariant ... See more keywords
LUIFT: LUminance Invariant Feature Transform
Sign Up to like & getrecommendations! Published in 2018 at "Mathematical Problems in Engineering"
DOI: 10.1155/2018/3758102
Abstract: Illumination-invariant method for computing local feature points and descriptors, referred to as LUminance Invariant Feature Transform (LUIFT), is proposed. The method helps us to extract the most significant local features in images degraded by nonuniform… read more here.
Keywords: luminance invariant; invariant feature; feature; feature transform ... See more keywords