Image purple fringe eliminating system, method, computer-readable storage medium, and photographing device
Disclosed in the present invention are an image purple fringe eliminating system, method, a computer-readable storage medium, and a photographing device. The system traverses an image, calculates a hue of a pixel, counts a ratio of purple hue to adjacent purple hue pixels in the image, and calculates a dynamic purple fringe detection threshold; creates a mask with the same size as the image acquired by an image acquisition module, and detects the pixels that fall into a purple fringe area; corrects the detected pixel falling into the purple fringe area, correcting both a red channel intensity value and a blue channel intensity value of the pixels within the purple fringe region using a green channel intensity value. The invention can automatically correct the purple fringe of the image, improve the image shooting quality and the user experience.
1. An image purple fringe eliminating method performed by a photographing device, comprising steps of:
acquiring an image;
traversing the acquired image and calculating hues of pixels, counting a ratio of pixels of purple and adjacent to purple in the image, and calculating a dynamic detection threshold value of purple fringe;
creating a mask with a same size as the acquired image, and detecting pixels within a purple fringe region;
correcting the detected pixels within the purple fringe region, and correcting both a red channel intensity value and a blue channel intensity value of the pixels within the purple fringe region using a green channel intensity value; and
outputting a corrected image.
2. The method of claim 1 , wherein a step of traversing the acquired image and calculating hues of pixels, specifically comprises:
traversing the acquired image, scanning all pixels one by one, and calculating a hue of a pixel according to the following formula:
h
=
{
60
°
×
r
-
b
max
-
min
+
240
°
if
max
=
b
&
b
-
g
>
25
60
°
×
g
-
b
max
-
min
+
360
if
max
=
r
&
r
-
g
>
25
0
else
where, h is a hue of a pixel; r, g, and b respectively represent a red channel intensity value, a green channel intensity value and a blue channel intensity value of pixels of an image, max represents a maximum intensity value of the three color channels, and min represents a minimum intensity value of the three color channels.
3. The method of claim 2 , wherein a step of counting a ratio of pixels of purple and adjacent to purple in the image, specifically comprises:
using a preset hue threshold value range of purple and adjacent to purple, counting a total number N of pixels of purple and adjacent to purple of which the hues are within the preset hue threshold value range, and calculating a ratio of the total number N of pixels of purple and adjacent to purple relative to pixels of the whole image using the formula:
ratio
=
N
Size
where Size represents a size of the image.
4. The method of claim 3 , wherein a step of calculating a dynamic detection threshold value of purple fringe, specifically comprises:
using the formula:
{
minPH
=
195
+
t
*
ratio
maxPH
=
315
-
t
*
ratio
and calculating a detection threshold value of purple fringe, where min PH, max PH represent a minimum hue threshold value and a maximum hue threshold value of purple fringe respectively, and parameter t is 20.
5. The method of claim 4 , wherein a step of creating a mask with a same size as the acquired image, and detecting pixels within a purple fringe region, specifically comprises:
creating a mask with the same size as the acquired image, and detecting all the pixels of which the hues are higher than the minimum hue threshold value and lower than the maximum hue threshold value of the purple fringe, and calculating the purple fringe region using the formula:
mask
(
i
,
j
)
=
{
255
minPH
<
h
<
maxPH
0
else
where mask(i,j)=255 represents the pixels falling into the purple fringe region, otherwise the pixels do not fall into the purple fringe region; min PH, max PH represent a minimum hue threshold value and a maximum hue threshold value of purple fringe respectively; thereby detecting pixels within the purple fringe region.
6. The method of claim 1 , wherein a step of correcting the detected pixels within the purple fringe region, and correcting both a red channel intensity value and a blue channel intensity value of the pixels within the purple fringe region using a green channel intensity value, specifically comprises:
correcting the red channel intensity value and the blue channel intensity value of the pixels within the purple fringe region using the formula:
{
r
corrected
=
λ
r
·
r
+
(
1
-
λ
r
)
·
g
0
<
λ
r
<
1
b
corrected
=
λ
b
·
b
+
(
1
-
λ
b
)
·
g
0
<
λ
b
<
1
,
where r, g, and b represent the red channel intensity value, the green channel intensity value and the blue channel intensity value respectively; r corrected , b corrected represent correction values of the red channel intensity value and the blue channel intensity value respectively; and λr, λ b represent parameters of the red channel and the blue channel, respectively.
7. A non-transitory computer readable medium, having stored thereon, a set of computer-executable instructions for causing one or more processors to perform steps of an image purple fringe eliminating method, comprising:
acquiring an image;
traversing the acquired image and calculating hues of pixels, counting a ratio of pixels of purple and adjacent to purple in the image, and calculating a dynamic detection threshold value of purple fringe;
creating a mask with a same size as the acquired image, and detecting pixels within a purple fringe region;
correcting the detected pixels within the purple fringe region, and correcting both a red channel intensity value and a blue channel intensity value of the pixels within the purple fringe region using a green channel intensity value; and
outputting a corrected image.
8. A photographing device, comprising:
one or more processors;
a non-transitory, computer readable memory;
a display screen; and
one or more computer-executable instructions;
wherein the processors are connected with the memory and display screen respectively by bus; the one or more computer-executable instructions are stored in the memory and are executable by the one or more processors to perform steps of an image purple fringe eliminating method, comprising:
acquiring an image;
traversing the acquired image and calculating hues of pixels, counting a ratio of pixels of purple and adjacent to purple in the image, and calculating a dynamic detection threshold value of purple fringe;
creating a mask with a same size as the acquired image, and detecting pixels within a purple fringe region;
correcting the detected pixels within the purple fringe region, and correcting both a red channel intensity value and a blue channel intensity value of the pixels within the purple fringe region using a green channel intensity value; and
outputting a corrected image.
9. The device of claim 8 , wherein a step of traversing the acquired image and calculating hues of pixels, specifically comprises:
traversing the acquired image, scanning all pixels one by one, and calculating a hue of a pixel according to the following formula:
h
=
{
60
°
×
r
-
b
max
-
min
+
240
°
if
max
=
b
&
b
-
g
>
25
60
°
×
g
-
b
max
-
min
+
360
if
max
=
r
&
r
-
g
>
25
0
else
where, h is a hue of a pixel; r, g, and b respectively represent a red channel intensity value, a green channel intensity value and a blue channel intensity value of pixels of an image, max represents a maximum intensity value of the three color channels, and min represents a minimum intensity value of the three color channels.
10. The method of claim 9 , wherein a step of counting a ratio of pixels of purple and adjacent to purple in the image, specifically comprises:
using a preset hue threshold value range of purple and adjacent to purple, counting a total number N of pixels of purple and adjacent to purple of which the hues are within the preset hue threshold value range, and calculating a ratio of the total number N of pixels of purple and adjacent to purple relative to pixels of the whole image using the formula:
ratio
=
N
Size
where Size represents a size of the image.
11. The method of claim 10 , wherein a step of calculating a dynamic detection threshold value of purple fringe, specifically comprises:
using the formula:
{
minPH
=
195
+
t
*
ratio
maxPH
=
315
-
t
*
ratio
and calculating a detection threshold value of purple fringe, where min PH, max PH represent a minimum hue threshold value and a maximum hue threshold value of purple fringe respectively, and parameter t is 20.
12. The method of claim 8 , wherein a step of creating a mask with a same size as the acquired image, and detecting pixels within a purple fringe region, specifically comprises:
creating a mask with the same size as the acquired image, and detecting all pixels of which hues are higher than the minimum hue threshold value and lower than the maximum hue threshold value of the purple fringe, and calculating the purple fringe region using the formula:
mask
(
i
,
j
)
=
{
255
minPH
<
h
<
maxPH
0
else
where mask(i,j)=255 represents the pixels falling into the purple fringe region, otherwise the pixels do not fall into the purple fringe region; min PH, max PH represent a minimum hue threshold value and a maximum hue threshold value of purple fringe respectively; thereby detecting pixels within the purple fringe region.
13. The method of claim 8 , wherein a step of correcting the detected pixels within the purple fringe region, and correcting both a red channel intensity value and a blue channel intensity value of the pixels within the purple fringe region using a green channel intensity value, specifically comprises:
correcting the red channel intensity value and the blue channel intensity value of the pixels within the purple fringe region using the formula:
{
r
corrected
=
λ
r
·
r
+
(
1
-
λ
r
)
·
g
0
<
λ
r
<
1
b
corrected
=
λ
b
·
b
+
(
1
-
λ
b
)
·
g
0
<
λ
b
<
1
,
where r, g, and b represent the red channel intensity value, the green channel intensity value and the blue channel intensity value respectively; r corrected , b corrected represent correction values of the red channel intensity value and the blue channel intensity value respectively; and λr, λ b represent parameters of the red channel and the blue channel, respectively.