DocumentCode :
290134
Title :
New prospects in line detection for remote sensing images
Author :
Merlet, N. ; Zerubia, J.
Author_Institution :
Inst. of Comput. Sci., Hebrew Univ., Jerusalem, Israel
Volume :
v
fYear :
1994
fDate :
19-22 Apr 1994
Abstract :
Dynamic programming is one of the main methods of line detection. It defines a cost, which depends on local information, and performs a summation-minimization process in a graph or in the image. In particular, Fischler et al. (1981) presented an algorithm called F*, which achieves important results (convergence, robustness, rapidity). In previous works, we proposed a mathematical formalization of the F*, which allowed us to extend the cost to cliques of more than two points to take into account the contrast, and to include curvature information in the cost by using neighborhoods of size larger than one. In the present paper, we propose a method for computing this cost automatically for a wide range of images, from the probability distribution in the neighborhood of sample segments. We apply the resulting potentials on SPOT images
Keywords :
dynamic programming; image recognition; image segmentation; minimisation; probability; remote sensing; SPOT images; algorithm; convergence; curvature information; dynamic programming; line detection; local information; probability distribution; remote sensing images; road detection; robustness; sample segments; summation-minimization process; Convergence; Cost function; Distributed computing; Dynamic programming; Electronic mail; Iterative algorithms; Iterative methods; Noise robustness; Probability distribution; Remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
ISSN :
1520-6149
Print_ISBN :
0-7803-1775-0
Type :
conf
DOI :
10.1109/ICASSP.1994.389381
Filename :
389381
Link To Document :
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