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Mapping without the sun
Zhang, Jixian

Figure 4. Segmented images
a-before-event, b-after-event
Figure 3. Correspondence region matching arithmetic
Figure 5. Change detetection results
a-Changed area, b-Omitted area, c-False alarm area
d-Visual interpretation result, e-Image differencing result
On comparing the ARs at the threshold of 15, the changed
regions are labelled on after-event images,delineated by
EafiSS.Overall accuracy is 89.73%,omission error is 5.79% and
commission error is 4.48%.
Visual interpretation is largely dependent on analysts’
expertise,which has a higher accuracy ,but is
time-consuming.As Figure 5. e shows,image differencing
mainly detects the edge of changed proportion and omitted
phenomena is very severe.Moreover, the wholeness of changed
area is bad and “salt and pepper” effect exists in the resulting
map.After the comparison,it is easy to find that region-based
change detection method has higher accuracy than pixel-based
approaches, a little inferior to the visual interpretation result,but
is time-saving.
With the popularization of high resolution image
resources,region-based change detection methods close to
human visual interpretation characteristic has a bright future.lt
is proved that the technique proposed in this research detects
object-specific changes effectively with a accuracy above
85%.Furthermore,this method compares regionsfnot pixels)
features so that it is not sensitive to the accuracy of image
registration.Also,Features are not relatated to the characteristic
of images radiance and the acquisition way so as to combine