Title :
Automated Detection of Martian Dune Fields
Author :
Bandeira, Lourenço ; Marques, Jorge S. ; Saraiva, José ; Pina, Pedro
Author_Institution :
Centre for Natural Resources & the Environ., Inst. Super. Tecnico, Lisbon, Portugal
fDate :
7/1/2011 12:00:00 AM
Abstract :
An approach for the automated detection of dune fields on remotely sensed images of the surface of Mars is presented in this letter. It is based on the extraction of local information from images (i.e., gradient features), which, in turn, is tested with boosting and support vector machine classifiers. A detection rate of about 95% is obtained for fivefold cross validation on a set of 78 panchromatic images captured by the Mars Orbiter Camera of the Mars Global Surveyor probe on different locations of the planet.
Keywords :
Mars; astronomical image processing; planetary surfaces; Mars Global Surveyor probe; Mars Orbiter Camera; martian dune field detection; remotely sensed image; support vector machine classifier; Boosting; Feature extraction; Histograms; Mars; Pixel; Remote sensing; Support vector machines; Boosting; Mars; dunes; histogram of oriented gradient (HOG) features; support vector machine (SVM);
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2010.2098390
