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EXPERIMENT ON PRODUCING DISPARITY MAPS FROM AERIAL STEREO IMAGES USING UNSUPERVISED AND SUPERVISED METHODS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Recent advancement in hardware and software provides the possibility of realizing full automation in stereo-image tasks. This paper investigated disparity map generation from aerial images with different methods: unsupervised method and supervised ...
L. Zhu +3 more
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Stereo Matching with Nonlinear Diffusion [PDF]
International Journal of Computer Vision, 1996 One of the central problems in stereo matching (and other image registration tasks) is the selection of optimal window sizes for comparing image regions. This paper addresses this problem with some novel algorithms based on iteratively diffusing support at different disparity hypotheses, and locally controlling the amount of diffusion based on the ...
Scharstein, Daniel, Szeliski, Richard
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Stereo sensitivity depends on stereo matching
Journal of Vision, 2005 Stereoacuity thresholds, measured with bar targets, rise as the absolute disparity of the bars is increased. One explanation for this rise is that, as the bars are moved away from the fixation plane, the stereo system uses coarser mechanisms to encode the bars' disparity; coarse mechanisms are insensitive to small changes in target disparity, resulting
Suzanne P, McKee +2 more
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HIGH-PRECISION DEM PRODUCTION FOR SPACEBORNE STEREO SAR IMAGES BASED ON SIFT MATCHING AND REGION-BASED LEAST SQUARES MATCHING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Generally, there are two ways to generate Digital Elevation Model (DEM) using synthetic aperture radar (SAR) data, which are Interferometer Synthetic Aperture Radar(InSAR) and radargrammetry. Considering the disadvantages of InSAR data, such as the limit
S. Xiaotian, Z. Guo, Z. Guo, W. Xia
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Pyramid Stereo Matching Network [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Recent work has shown that depth estimation from a stereo pair of images can be formulated as a supervised learning task to be resolved with convolutional neural networks (CNNs). However, current architectures rely on patch-based Siamese networks, lacking the means to exploit context information for finding correspondence in illposed regions. To tackle
Jia-Ren Chang, Yong-Sheng Chen
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A Low-Complexity End-to-End Stereo Matching Pipeline From Raw Bayer Pattern Images to Disparity Maps
IEEE Access, 2021 Conventional computer vision algorithms, including stereo matching algorithms, take finely rendered color images as input. However, existing image signal processing (ISP) pipelines for color image generation are designed for photography with a goal of ...
Shengyu Gao, Hongyu Wang, Xin Lou
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Single View Stereo Matching [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Previous monocular depth estimation methods take a single view and directly regress the expected results. Though recent advances are made by applying geometrically inspired loss functions during training, the inference procedure does not explicitly impose any geometrical constraint.
Yue Luo +6 more
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Segment-based adaptive window and multi-feature fusion for stereo matching
Journal of Algorithms & Computational Technology, 2016 As to the problems of local stereo matching methods, such as matching window selection difficulty, fuzzy disparity edges and low accuracy in weak texture regions, this paper proposes an efficient stereo matching algorithm to improve the stereo matching ...
Hua Shi +4 more
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Coarse-to-Fine Stereo Matching Network Based on Multi-Scale Structural Information Filtrating
IEEE Access, 2023 Stereo vision measurement is widely applied in tasks such as autonomous driving and 3D scene reconstruction. Accurately obtaining the disparity of stereo images relies on effective stereo matching algorithms.
Yuanwei Bi +5 more
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Estimation of disparity map of stereo image pairs using spatial domain local Gabor wavelet
IET Computer Vision, 2015 The stereo matching problem takes two images captured by nearby cameras and attempts to recover quantitative disparity information. Most of the existing stereo matching algorithms find it difficult to estimate disparity in the occlusion, discontinuities ...
T. Malathi, M.K. Bhuyan
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