429
a) Image with gauss noise
b) MRED algorithm
c) Sobel algorithm
d) Pal.King algorithm e) FGED algorithm f) WFCE algorithm
Figure4 Contrastive test of five algorithms in 10% gauss noise
i appears over
iject is cannot
rED algorithm is
affected by noise
gauss noise, the
tuns in different
Compare the detect result, we find that the MRFD algorithm
have an obviously relatively superiority of antinoise capability
in edge detection of multispectral image.
An edge detection algorithm for multispectral RS image
(MRED) is proposed based on the detailed analysis of the
characters of multispectral image. Through the multi
dimensional cloud-space mapping model the objects in image
can be mapped to the cloud-space, the fuzzy feature matrix that
covered by multi-dimensional edge cloud is extracted by
Boolean calculation between intersectant clouds. Calculating
image fuzzy division entropy by fuzzy feature matrix of each
sub-cloud space, bring stochastic influence of image into
solution of entropy and use fuzzy division entropy repeatedly to
find the best result in membership. The edge map with
preferable precision can be obtain by integrate the detect result
of every sub-cloud space. MRED algorithm considering fuzzy
features of remote sensing image and discussing the connatural
stochastic of image at the same time, the contrastive test is
proved that this algorithm is more effective than contrastive
algorithm on detection quality and antinoise.
ACKNOWLEDGMENTS
The work is supported by Chongqing Nature Science Fund
(CSTC 2007BB2392).
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