Perceptual luminance nonlinearity-based image data exchange across different display capabilities
A handheld imaging device has a data receiver that is configured to receive reference encoded image data. The data includes reference code values, which are encoded by an external coding system. The reference code values represent reference gray levels, which are being selected using a reference grayscale display function that is based on perceptual non-linearity of human vision adapted at different light levels to spatial frequencies. The imaging device also has a data converter that is configured to access a code mapping between the reference code values and device-specific code values of the imaging device. The device-specific code values are configured to produce gray levels that are specific to the imaging device. Based on the code mapping, the data converter is configured to transcode the reference encoded image data into device-specific image data, which is encoded with the device-specific code values.
1. A method performed on one or more processors comprising:
receiving a perceptual curve digital code value D for an image;
determining a normalized perceptual curve signal value V from a perceptual curve digital code value D determining a normalized color component value C based on a functional model of
C
=
(
max
[
(
V
1
m
-
c
1
)
,
0
]
c
2
-
c
3
V
1
m
)
1
n
;
determining an absolute value L from at least the normalized component value C,
wherein parameters n, m, c 1 , c 2 , and c 3 are predetermined values; and
rendering the image based on the determining of the absolute value L.
2. The method of claim 1 , wherein:
n
=
2610
4096
×
1
4
≃
0.1593017578125
;
m
=
2523
4096
×
128
≃
78.84375
;
c
1
=
c
3
-
c
2
+
1
=
3424
4096
≃
0.8359375
;
c
2
=
2413
4096
×
32
≃
18.8515625
;
and
c
3
=
2392
4096
×
32
≃
18.6875
.
3. The method of claim 1 , wherein the perceptual curve digital code value D is 10 bits.
4. The method of claim 1 , wherein the perceptual curve digital code value D is 12 bits.
5. The method of claim 1 , wherein a relationship between the normalized perceptual curve signal value V and the perceptual curve digital code value D is provided by the function:
V
=
D
-
4
·
2
b
-
10
1015
·
2
b
-
10
,
wherein b is a bit depth corresponding to a number of bits used to represent the perceptual curve digital code value D.
6. The method of claim 1 wherein the perceptual curve digital code value D is received from a non-transitory storage media.
7. The method of claim 1 wherein the normalized color component value C is a red (R), green (G), or blue (B) component.
8. A method performed on one or more processors comprising:
receiving a perceptual curve digital code value D for an image;
determining a normalized perceptual curve signal value V from a perceptual curve digital code value D;
determining a normalized luminance value Y based on a functional model of
Y
=
(
max
[
(
V
1
m
-
c
1
)
,
0
]
c
2
-
c
3
V
1
m
)
1
n
;
determining an absolute value L from the normalized luminance value Y, wherein parameters n, m, c 1 , c 2 , and C 3 are predetermined values; and
rendering the image based on the determining of the absolute value L.
9. The method of claim 8 wherein L=10,000·Y.
10. The method of claim 8 , wherein:
n
=
2610
4096
×
1
4
≃
0.1593017578125
;
m
=
2523
4096
×
128
≃
78.84375
;
c
1
=
c
3
-
c
2
+
1
=
3424
4096
≃
0.8359375
;
c
2
=
2413
4096
×
32
≃
18.8515625
;
and
c
3
=
2392
4096
×
32
≃
18.6875
.
11. The method of claim 8 , wherein the perceptual curve digital code value D is 10 bits.
12. The method of claim 8 , wherein the perceptual curve digital code value D is 12 bits.
13. The method of claim 8 , wherein a relationship between the normalized perceptual curve signal value V and the perceptual curve digital code value D is provided by the function:
V
=
D
-
4
·
2
b
-
10
1015
·
2
b
-
10
,
wherein b is a bit depth corresponding to a number of bits used to represent the perceptual curve digital code value D.
14. The method of claim 8 wherein the perceptual curve digital code value D is received from a non-transitory storage media.