A Fast Dense Feature Tracking Routine with its Application in Cryosphere Remote Sensing Using Sentinel-1 and Landsat-8 Data
| Autor: | Piyush Agram, Alex S. Gardner, Yang Lei |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Radar tracker
010504 meteorology & atmospheric sciences Pixel Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Stereographic projection 010502 geochemistry & geophysics 01 natural sciences Universal Transverse Mercator coordinate system law.invention Geogrid Geolocation Lidar law Radar imaging Geocoding Cryosphere Cartesian coordinate system Radar 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | IGARSS |
| DOI: | 10.1109/igarss39084.2020.9323412 |
| Popis: | In this paper, we present a fast and intelligent routine for dense feature tracking with almost two orders of magnitude runtime improvement over conventional dense cross-correlation techniques. This routine consists of two novel modules: 1) “autoRIFT”, an efficient and intelligent dense cross-correlater with nested grid design, sparse/dense combinative searching strategy and disparity filtering technique; 2) “Geogrid”, the precise geocoding component that supports pointwise mapping between imaging coordinates (pixel location and displacement) and geographic Cartesian coordinates (geolocation and displacement velocity). autoRIFT can run on a grid in the native imaging coordinates (such as radar or map) and, when used in conjunction with the Geogrid module, on a user-defined grid in a geographic Cartesian coordinate system such as Universal Transverse Mercator or Polar Stereographic. Here we demonstrated its application in tracking ice displacement and validated with ESA's Sentinel-1A/B radar and NASA's Landsat-8 optical data. |
| Databáze: | OpenAIRE |
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