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kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images
2018
Remote Sensing
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It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. ...
Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. ...
Conflicts of Interest: The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish ...
doi:10.3390/rs10030432
fatcat:ue6ltoef7bc2bl7t4elmsp354i
KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION
2016
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. ...
This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization. ...
ACKNOWLEDGEMENTS (OPTIONAL) This work was supported by the National High Technology Research and Development Program (863) of China under Grant 2013AA12A301. ...
doi:10.5194/isprsannals-iii-1-49-2016
fatcat:d6rmslfxmjepzd7vj5jzmavgji
Comparison of Keypoint Detectors and Descriptors for Relative Radiometric Normalization of Bitemporal Remote Sensing Images
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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This paper compares the performances of the most commonly used keypoint detectors and descriptors (SIFT, SURF, KAZE, AKAZE, ORB, and BRISK) in keypoint-based Relative Radiometric Normalization (RRN) of ...
unregistered bitemporal multi-spectral images. ...
INTRODUCTION R ELATIVE Radiometric Normalization (RRN) is the process of rectifying radiometric distortions of a multi-band subject image with respect to a multi-band reference image, acquired by inter ...
doi:10.1109/jstars.2021.3069919
fatcat:f5kavbosx5ef5eaizbsscc6gwe
Deep Learning-Based Change Detection in Remote Sensing Images: A Review
2022
Remote Sensing
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Images gathered from different satellites are vastly available these days due to the fast development of remote sensing (RS) technology. ...
These images significantly enhance the data sources of change detection (CD). ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs14040871
fatcat:myyprcrcyzh6fhjz5ggqdc5e54
Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods
2013
IEEE Signal Processing Magazine
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to specific real applications involving audio processing for music genre prediction and hyperspectral satellite images for Earth and climate monitoring. ...
as their non-linear extensions derived by means of the theory of reproducing kernel Hilbert spaces. ...
Specific versions of kernel methods to deal with signal processing applications have also been proposed, such as the temporal kCCA of [27] , which is designed to exploit temporal structure in the data ...
doi:10.1109/msp.2013.2250591
fatcat:fxcugxbr6bfzfgkroedwf23ddu
Interoperability, XML Schema
[chapter]
2017
Encyclopedia of GIS
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For satellite images, radiometric correction techniques can be used. ...
ENVI software (ITT Visual Information Solutions, Boulder, CO) has a good technique for radiometric corrections of satellite images. 2. ...
A slight variant of this scheme considers square-shaped cluster candidates, instead of circularly shaped clusters: simply use a distance function based on the sum of coordinates, instead of the usual Euclidean ...
doi:10.1007/978-3-319-17885-1_100625
fatcat:bgxdhdxa4bewzcggrogz56rdpi
Adversarial approaches to remote sensing image analysis
[article]
2020
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We collected satellite images and ancient text descriptions for training in order to evaluate the efficacy of the proposed method. ...
The qualitative and quantitative results obtained suggest that the doc2vec encoder-based model yields better images in terms of the semantic agreement with the input description. ...
In the context of change detection, Volpi et.al [82] used a regularized kernel canonical correlation analysis transform (kCCA) to perform pixelwise alignment of multi-temporal cross sensor images. ...
doi:10.15168/11572_257100
fatcat:o3qb4wb4jjfbxnizkniqurc4pu