Image Processing Reference
In-Depth Information
tributes. According to the indiscernibility relation concept, the mammogram is divided into
two sub-images:
(1)
(2)
where
P
is the gradient threshold,
Q
is the noise threshold,
f
(
i
,
j
) is the gradient value calcu-
lated from the label-removed image, “
s
” denotes the sub-block. Considering
s
mn
as each pixel
examine its neighbors to decide whether it is noise or not. If it is, then eliminate the noise by
replacing the pixel value with
Q
. The sub-images that need to be enhanced are defined as fol-
lows:
(3)
(4)
Next, we enhance
I
1
and
I
2
, respectively, and get the final image by merging the sub-images:
I
2
is enhanced by histogram equalization method and
I
1
is transformed below:
(5)
Here, we set
ρ
=
γ
= 1.5. After enhancement, the boundary contrast between the mass and
surrounding tissue becomes more obvious.
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