DMCA
A COMBINED ESTIMATION-DEFORMATION MODEL FOR AREA DETECTION: APPLICATION TO TOPOGRAPHIC AREA FEATURE UPDATE
BibTeX
@MISC{_acombined,
author = {},
title = {A COMBINED ESTIMATION-DEFORMATION MODEL FOR AREA DETECTION: APPLICATION TO TOPOGRAPHIC AREA FEATURE UPDATE},
year = {}
}
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Abstract
This paper presents a fully automated approach for area detection based on multi-spectral images and features from a topographic database. The vectors residing in the database are refined using active contours (snakes) according to updated information provided by the multi-spectral images. The conventional methods of defining the external energy of the snake based on statistical measures or gradient-based boundary finding are often corrupted by poor image quality. Here a method to integrate the two approaches is proposed using an estimation of the maximum a posteriori (MAP) segmentation in an effort to form a unified approach that is robust to noise and poor edges. We further propose to improve the accuracy of the resulting boundary location an update of the snake topology. A number of experiments are performed on both synthetic and LANDSAT 7 images to evaluate the approach. 1.
Keyphrases
combined estimation-deformation model area detection application topographic area feature update multi-spectral image snake topology external energy poor edge boundary location area detection statistical measure poor image quality updated information active contour gradient-based boundary finding unified approach conventional method topographic database
