A new approach to classification of ground background using MSS images
Background Region Partition
The background segmentation is fulfilled by making use of the region growth principle and the pyramid data structure. We support the original image is N by N, and N = 2
m, it can divide into m+1 levels, each of which is also divided into some small regions using the same data structure. As dealing with the kth level, the membership of a subregion to the known category i is.
where
J
k (x,y,i) is the membership of the subregion in the kth level, the coordinate of whose center is (x,y) to the ith category,
J
m (x,y,i) is the average membership of all pixels in the original image to the ith category,
J
o (x,y,i) is the average membership of all pixels in the original image to the ith category,
The procedure for calculating the membership of each pixel in the original image to the sets I(x,y), and
(a) Calculating the sets I(x,y) and
Where
C: the number of category in the original image,
j: 1,2,……….C
g(x,y) ; the grey value of the (x,y) pixel in the original image
V
j: the average grey value of the jth category in the original image.
d
j: the distance between the (x,y) pixel and the clustering center of the jth category
(b). calculating the membership U
i(x,y)
if I(x,y) = {
f}, then
Where
i = 1,2,.........C
U
i(x,y): the membership of the (x,y) pixel in the original image to the ith category.
Conclusion
A method of the background region segmentation is presented in this paper. All algorithms written
by C language have been run on the Micro Vax - II computer system. A result is shown in Fig. 1 which satisfied the practical use in the different terrain classification.
Acknowledgement
We would like to thank Prof. W.T. Wu for his useful help and comments of the earlier draft.
References
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- Tou, Pattern Recognition Principles. Addison-Welsely Publishing company, 1974.
- Swain, S.M. Davis, Remote Sensing: THE Quantitative Approach, McGram-Hill company, 1987.
