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kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images

Yang Bai, Ping Tang, Changmiao Hu
2018 Remote Sensing  
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


Yang Bai, Ping Tang, Changmiao Hu
2016 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
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

Armin Moghimi, Turgay Celik, Ali Mohammadzadeh, Huseyin Kusetogullari
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
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

Ayesha Shafique, Guo Cao, Zia Khan, Muhammad Asad, Muhammad Aslam
2022 Remote Sensing  
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

Jeronimo Arenas-Garcia, Kaare Brandt Petersen, Gustavo Camps-Valls, Lars Kai Hansen
2013 IEEE Signal Processing Magazine  
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  
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]

Bejiga Mesay Belete
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 [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