16
7 8 9
10
12
Fig. 6 Hegions merged after completion of Stage Ila.
The removed boundaries are represented by dotted lines. Re-
gion 1 and 2 are merged forming region 14, and region 3,
4, 5 and 11 are merged forming region 16.
Region 10 is non-significant and must be merged. The
neighbour yielding the lowest merging t-score is 12. So, 10
is merged with 12, forming 18. The final result of Stage I
and Stage II is shown in fig. 7.
14
17
18
Fig. 7 Final result of our entire edge based region grow-
ing scheme. In Stage IIb region 6 is merged, due to its small
size, with region 16, the most similar neighbour, forming re-
gion 17. In Stage Ilc region 10, which is due to a mized
pizels boundary, is found insignificant and merged with re-
gion 12, forming region 18.
6 Experimental Results
We have implemented the procedure within DIGIS, our in-
door developed image processing software package, presently
running on a SUN 3/60 workstation. The programs are
written in FORTRAN-77, and consist of two independent
modules corresponding with the prediction stage (Stage I)
and the merging stage (Stage II).
798
6.1 The Test Images
We have tested our method on a number of artificial and
real images. We use two artificial images, see fig. 8 and
fig. 9. The contrast Ag between background g, and object
go is uniformly set to 100; g, = 75 and g, = 175, for both
SB and PV1. Notice that the border pixels of PV1 are re-
ally mixed pixels, in contrast with common synthetic test
images, which makes our test images much more realistic.
The images are contaminated by a zero-mean Gaussian dis-
tributed pseudo-random noise field generated by computer,
with o,, = 10,20, and 50, resulting in a signal-to-noise ratio
SNR = Ag*/02 = 100,25, and 4, respectively. We use two
real images, see fig. 10 and fig. 11.
To reduce the noise, the image may be preprocessed by
several types of smoothing filters (see section 3). Each filter
has window size 3 x 3 and is applied non-iteratively. The
threshold of the conditional average filter is set to 30.
6.2 Artificial Images
SB images To demonstrate the entire experimentation,
the SB image is treated in length. Fig. 8a gives the ideal SB
image. Fig. 8b is the image after adding a o, = 50 noise
field, and fig. 8c shows the result of the 3 x 3 extended
Kuwahara filter on fig. 8b. This is the input image for
Stage I.
f
Fig. 8 SB image, size 64?, a) ideal image; b) ideal
image corrupted with a o, — 50 noise field; c) result of
eztended Kuwahara smoothing on b; d) result of Stage I,
the prediction stage; e) final result of Stage II, the merging
stage; f) outline of the regions.
tic
99
th:
ea
sm
sin
are
reg
dis
20
alr
sm
Stz
the