Simultaneous segmentation of multiband images
- Search the least weighted link in the graph and satellite from two vertices which connected value by this least weighted link the difference between maximum and minimum of intensity value.
In the same time the difference between maximum and minimum intensity value from the two corresponding pixels (or regions) in the other bands will also be calculated the least weighted link will be removed if all the differences values which are calculated from this step is less than the given homogeneity threshold value then the higher segmented region will be formed by agglomerating these two vertices (or regions).
On the contrary if the difference value from any bands is not less than the given homogeneity property, the two vertices (or regions) still separate.
- Repeat the step (4) until the last least weighted link the final result will give a segmented image which can image supper imposed to all of the image band and each super imposed segmented region of each image band is satisfied the given homogeneity property.
Implementation example
In this section, the proposed algorithm for simultaneous segmentation
of multi band images is applied to the land sat imageries shown in
fig 3 the algorithms is implemented on a micro computer IBM PC /AT
compatible we apply the graph theory to the band since it gives the
highest contrast after processing according to the procedure in the
section 2 we obtain the super imposed segmented image as shown in
fig 4 where the given homogeneity threshold value (
Î) is chosen to be equal to 18 while in the figures 5 shows a random coloured classification from the mean value of segmented region from our algorithm.
Fig.3 Landsat multispectral images over the Bangkok area,
(a) band 4, (b) band 5, (c) band 6 and (d) band 7.
