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mod1
Figure 1 Left is a simple model of a high amplitude salt boundary. Right is the partitioned output of the segmentation method.
On the left in Figure
is a simple model of a salt boundary. The vertical stripe in the middle is the high amplitude salt reflection. The results of the segmentation method can be seen on the right. The pixels have been partitioned into two groups, one on either side of the boundary.
mod2
Figure 2 Left is a simple model of a high amplitude discontinuous salt boundary. Right is the partitioned output of the segmentation method.
On the left in Figure
is the same simple model as Figure
yet with a discontinuity. Notice that the output result on the right partitions the image across the discontinuity. Although only a simple test case, this demonstrates that this segmentation method can successfully partition data where the amplitude is discontinuous.
The resulting
eigenvector for the discontinous model is shown on the left in Figure
. It is this eigenvector that is used to partition the data. The splitting point is at zero. All values greater than zero will be in one group and all values less than zero in the other group. However, a practical measure recommended by Shi and Malik (2000) is to calculate the normalized cut at several splitting points across the eigenvector and take the minimum. On the right in Figure
is a contour plot of the
eigenvector. Each contour can be thought of as the partition for a different splitting point. Notice that the contours are spread out in the area of the discontinuity. Here the algorithm is unsure of where to track the salt boundary and basically opts for the shortest distance.
y2_2
Figure 3 Left the
eigenvector of Figure
. Right is a contour plot of the
eigenvector.
unocal
Figure 4 A 2D seismic section from Unocal. The major reflection at 3200 ms is the salt boundary.
unocal.amp
Figure 5 This is the instantaneous amplitude of the seismic section in Figure
.
out_y
Figure 6
eigenvector calculated from the data in Figure
.
cont_y
Figure 7 A contour plot of the
eigenvector in Figure
. Notice the areas of uncertainty where the contours are spreading.
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Stanford Exploration Project
10/14/2003