Application of Feature Tracking Using <italic>K</italic>-Nearest-Neighbor Vector Field Consensus in Sea Ice Tracking

Application of Feature Tracking Using <italic>K</italic>-Nearest-Neighbor Vector Field Consensus in Sea Ice Tracking

A feature-tracking algorithm algorithm utilizing the proposed <italic>K</italic>-nearest-neighbor vector field consensus (KVFC) to filter outliers is developed to monitor the dynamic changes of sea ice retrieval from synthetic aperture radar (SAR) images. The KVFC is based on vector fiel...

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Bibliographic Details
Main Authors: Bin He, Xi Zhao, Ying Chen, Chuang Liu, Xiaoping Pang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Correspondences
feature
<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$K$</tex-math> </inline-formula> </named-content>-nearest-neighbor vector field consensus (KVFC)
sea-ice drift
synthetic aperture radar (SAR)
Online Access:https://ieeexplore.ieee.org/document/9783199/

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https://ieeexplore.ieee.org/document/9783199/

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