X-ray or gamma ray systems or devices – Specific application – Absorption
Reexamination Certificate
2002-06-13
2004-11-02
Bruce, David V (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Absorption
C382S130000, C382S131000, C378S008000
Reexamination Certificate
active
06813335
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to an image processing apparatus, image processing system, and image processing method, a program, and a computer readable storage medium that stores the program, for executing an image processing for an objective image.
BACKGROUND OF THE INVENTION
Conventionally, for example, a chest image obtained by X-ray photography has a very broad range of pixel values since it is made up of an image region of lungs which readily transmit X-rays, and an image region of a mediastinal part which hardly transmit X-rays. For this reason, it has been considered to be difficult to obtain a visualized X-ray chest image that allows to simultaneously observe image portions of both the lungs and mediastinal part.
As a method of avoiding this problem, an image processing method described in Japanese Patent Laid-Open No. 2000-101841 or the like is known. This image processing method is described using an original image f(x, y), an image fh(x, y) after tone conversion of the original image f(x, y), an image fc(x, y) after compression of the original image f(x, y), a low-frequency image (smoothed image) Sus(x, y) of the original image f(x, y), and a constant B by:
fc
(
x
,
y
)
=
F
(
f
(
x
,
y
)
)
+
B
×
(
1
-
∂
F
(
f
(
x
,
y
)
)
∂
f
(
x
,
y
)
)
×
(
f
(
x
,
y
)
-
Sus
(
x
,
y
)
)
(
1
)
Sus
(
x
,
y
)
=
∫
-
d1
d1
∫
-
d2
d2
f
(
x
+
x1
,
y
+
y1
)
ⅆ
x1
ⅆ
y1
∫
-
d1
d1
∫
-
d2
d2
ⅆ
x1
ⅆ
y1
(
2
)
In equation (1),
f(x, y)−Sus(x, y)
represents high-frequency components. By the effect of the second term of equation (1) including this part, the amplitudes of the compressed high-frequency components are restored or reconstructed (when B=1) and, hence, the appearance of a microstructure mainly formed by the high-frequency components can be maintained as in the original image f(x, y) even after compression of the dynamic range.
Note that “F( )” is a monotone increasing function indicating a tone conversion curve. The tone conversion curve F( ) is defined to be continuous and differentiable. With this method, the dynamic range of image data can be compressed while maintaining the amplitudes of high-frequency components (when B=1).
Note that the low-frequency image “Sus(x, y)” given by equation (2) is a moving average image of the original image f(x, y).
As an image process for making the microstructure easy to see, a so-called sharpening process is known. This sharpening process is described using the original image f(x, y), a processed image fp(x, y), a low-frequency image Sus
2
(x, y) of the original image f(x, y), and a constant C by:
fp
(
x, y
)=
f
(
x, y
)+
C
×(
f
(
x, y
)−
Sus
2
(
x, y
)) (3)
Note that the low-frequency image Sus
2
(x, y) has a mask size different from the low-frequency image Sus(x, y) given by equation (2).
As another image process, a noise removal process for reducing noise by removing or suppressing predetermined high-frequency components have been examined.
However, with the conventional image processing method, all of a plurality of image processes such as the aforementioned dynamic range compression process, sharpening process, noise removal process, and the like cannot be satisfactorily done for an original image.
More specifically, when the original image f(x, y) undergoes the sharpening process, and then the dynamic range compression process, equation (1) is rewritten as:
fc
(
x
,
y
)
=
F
(
fp
(
x
,
y
)
)
+
B
×
(
1
-
∂
F
(
f
(
x
,
y
)
)
∂
f
(
x
,
y
)
)
×
(
fp
(
x
,
y
)
-
Sus3
(
x
,
y
)
)
(
4
)
In this equation (4),
fp(x, y)−Sus
3
(x, y)
represents the high-frequency components of the image fp(x, y) after the sharpening process.
However, the low-frequency image Sus
3
(x, y) of the image fp(x, y) after the sharpening process is influenced by the term including “Sus
4
(x, y)”, as described by:
Sus3
(
x
,
y
)
=
∫
-
d1
d1
∫
-
d2
d2
fp
(
x
+
x1
,
y
+
y1
)
ⅆ
x1
ⅆ
y1
∫
-
d1
d1
∫
-
d2
d2
ⅆ
x1
ⅆ
y1
=
(
1
+
c
)
×
Sus
(
x
,
y
)
-
c
×
Sus4
(
x
,
y
)
(
5
)
Sus4
(
x
,
y
)
=
∫
-
d1
d1
∫
-
d2
d2
sus2
(
x
+
x1
,
y
+
y1
)
ⅆ
x1
ⅆ
y1
∫
-
d1
d1
∫
-
d2
d2
ⅆ
x1
ⅆ
y1
(
6
)
and is different from high-frequency components given by:
f(x, y)−Sus(x, y)
in equation (1), and high-frequency components given by:
fp(x, y)−Sus
3
(x, y)
in equation (4).
Therefore, the dynamic range compression process described by equation (1), and that described by equation (4) have different high-frequency bands to be restored and different restorabilities of the microstructure, and such differences may deteriorate image quality. The same problem is experienced when the sharpening process is done after the dynamic range compression process.
That is, when a frequency process using a low-frequency image obtained by calculating a moving average or the like is done twice or more, the same problem is posed irrespective of what sharpening and dynamic range compression processes are used. Since the visible characteristics of a human being for high-frequency components change depending on the density (luminance) level, and the dynamic range compression process changes the density (pixel value) level of at least a partial region of an image, the effect of the sharpening process is influenced by the dynamic range compression process.
The noise removal process basically suppresses high-frequency components, while the sharpening process emphasizes high-frequency components. That is, the noise removal process and sharpening process have conflicting effects.
Therefore, in a conventional arrangement in which the noise removal process and sharpening process are independently done, a region where high-frequency components are to be suppressed may be emphasized, or a region where high-frequency components are to be emphasized may be suppressed. Such problem directly leads to deterioration of image quality.
Also, the sharpening process described by equation (3) cannot emphasize a specific frequency band (e.g., one or a plurality of predetermined middle frequency bands). Hence, an image process such as a sharpening process may be executed using a multiple-frequency process that can easily adjust (emphasize and/or suppress) the specific frequency band). In this case as well, the same problem as described above remains unsolved upon executing a plurality of different image processes such as a process for changing the dynamic range, sharpening process, and the like.
For example, a plurality of different image processes such as a dynamic range change process, sharpening process, and the like must be appropriately mixed to assure restorability of image components in a specific frequency band or allow an easy frequency emphasis or suppression process that the user intended.
SUMMARY OF THE INVENTION
The present invention has been made to solve the above problems, and has as its object to provide an image processing apparatus, image processing system, and image processing method, a program, and a computer readable storage medium that stores the program, which can systematically, efficiently, and appropriately execute a plurality of image processings.
It is another object of the present invention to provide an image processing apparatus, image processing system, and image processing method, a program, and a computer readable storage medium that stores the program, which can obtain a stable image processing effect.
In order to achieve the above objects, an image processing apparatus according to the present invention comprises the following arrangement. That is, there is provided an image proce
Bruce David V
Canon Kabushiki Kaisha
Fitzpatrick ,Cella, Harper & Scinto
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