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Mapping without the sun
Zhang, Jixian

2.4m multispectral
1094X886 pixels
SAR and optical images fusion
based on wavelet transform
Registration to “ before ” using 60
ground control points with first
order polynomial transform
2.4m multispectral
1166X843 pixels
Table 1. High-resolution QuickBird imagery of Bam
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Figure 1. ENVISAT ASAR data in Bam
Object-based change detection method avoids the disadvantage
of pixel-based approaches and is more suitable for high
resolution satellite images.The technique workflow as
follows(Figure 2).
First of all, images from different and same sensors are
registered to each other. SAR and optical images fusion based
on wavelet transform is executed on CASMImageinfo3.0.And
then multiresolution segmentation divides the processed images
into homogeneous regions ,r'espectively.Make sure that the
number of before event image regions is more than that of after
event image regions in order for the characteristic consistency
of regions.After that,region features which represent elements
accurately and exclusively are extracted,including(l)spectral
feature:mean,(2)shape featurexentral geographic coordinate and
mininmal ex-rectangle of regions,(3)texture feature:gray-level
co-occurance matrix. In order to eliminate the influence of
shadow on final results,those are labeled by
human-assissted.According to the segmented before-event
image regions(exclusive of shadow regions) centriods,we use
ARs searching method proposed in this paper to look up ARs on
after-event ones.Repetition is executed for those which haven’t
been corresponded on after-event images.Thus all regions
between before-event and after-event images have
one-against-one relationship.Afterwards the feature space
distance is calculated between the ARs. Finally, threshold
defined by users determines whether regions change or not.
4.1 Multiresolution Segmentation
Segmentation is an important method for acquiring
objects.Multiresolution segmentation is a bottom-up
region-merging technique starting with one-pixel objects.In
numerous subsequent steps,image objects are merged into
bigger ones.Throughout this pairwise clustering process,the
heterogeneity criterion is considered,defined by scale
parameter.If the smallest growth exceeds the scale parameter,the
merging process stops.This heterogeneity criterion is a weighted
by the mean between spectral heterogeneity (hc 0lor )and spatial
heterogeneity(h shape ). The definition as follows:
h = W * Kotor + 0 — w) • Khope (1)
where w=color weight(against shapejwith 0 < W < 1
4.2 ARs Searching Based On Minimum Ex-rectangle
ARs searching is the premises of region feature comparison.If
not,many false alarms will generate so as to reduce the detection
The arithmetic workflow(Figure 3) is delineated as follows:We
establish correspondence relationship for all regions between
before and after event images according to region centroids.
There are three kinds of result:one against none(l-a-0),one
against one(l-a-l) and one against rest(l-a-r).As for the case of
l-a-r,the offsets between correspondence regions centroids are
calculated.In the images pre-processing step,we have the
pro-knowledge of the accuracy of image registration between
before and after event images.Therefore,we can estimate the
association confidence and establish the correspondence
4.3 Region Features Similarity Comparison Measured By
Feature Space Distance
The similarity of feature space between ARs is a key to
determine whether change or not.The similarity measurement is
not only consistent with human vision,easy to compute but also
robust for the accuracy of segmentation techniques.The distance
of feature space between ARs is a weighted mean between
spectral(brightness) and texture(gray-level co-occurence matrix)
factors. The distance is compared with threshold defined by
users,which is larger considered as changed,no change
4.4 Accuracy Assessment Using Simple Confusion Matrix
Accuracy assessment is a way to estimate the effectiveness of
change detection methods.There are two aspects: (1) attribute
accuracy,detecting change/no change and change type,(2)