Method and apparatus for reducing noise in an image using wavelet decomposition
A method of reducing noise in an image comprises decomposing the image to generate wavelet coefficients at different scales. The wavelet coefficients are then modified based on the energy of the wavelet coefficients at the different scales. The image is reconstructed based on the modified wavelet coefficients.
1. A method of reducing noise in an image comprising:
decomposing the image to generate wavelet coefficients at different scales;
modifying the wavelet coefficients based on the energy of the wavelet coefficients at said different scales; and
reconstructing the image based on the modified wavelet coefficients;
wherein during the decomposing, said image is decomposed into wavelet detail spaces at different scales, each wavelet detail space comprising a plurality of wavelet detail subbands and each wavelet detail subband comprising a matrix of wavelet coefficients; and
wherein during the modifying, the feature energy of the wavelet coefficients is determined according to:
FeatureEnergy
j
(
p
)
=
{
NISE
j
(
p
)
+
NeighborEnergy
j
(
p
)
j
<
J
0
SSE
j
(
p
)
+
NeighborEnergy
j
(
p
)
j
=
J
0
where NISE j (p) is the normalized inter-scale energy, SSE j (p) is the single scale energy, NeighborEnergy j (p) is the weighted average single scale energy, j is the scale and p is location (x,y) in each wavelet detail subband.
2. The method of claim 1 wherein said modifying is further based on an adjustable parameter.
3. The method of claim 2 wherein during said modifying each wavelet coefficient is multiplied by a shrinkage ratio of the form:
Shrinkage
j
(
p
)
=
{
1
FeatureEnergy
j
(
p
)
>
K
*
TH
j
(
FeatureEnergy
j
(
p
)
-
K
*
TL
j
)
K
*
TH
j
-
K
*
TL
j
0
FeatureEnergy
j
(
p
)
<
K
*
TL
j
where K is the adjustable parameter and TH j and TL j are thresholds for scale j.
4. The method of claim 3 wherein K is of the form:
K=log 2 (ISOsetting/NormalISO)/2
where ISOsetting is the ISO value of the image capture device used to capture the image and NormalISO is the typical ISO setting of the image capture device.
5. The method of claim 4 wherein said thresholds are determined by examining noise images captured at different ISO settings.
6. The method of claim 5 wherein said thresholds are based on the feature energy of wavelet coefficients of said noise images.
7. The method of claim 1 wherein said decomposing, modifying and reconstructing are performed independentlyon one or more channels of said image.
8. The method of claim 7 wherein said one or more channels comprises the Y channel of said image.
9. The method of claim 7 wherein said one or more channels comprises red and blue channels of said image.
10. The method of claim 1 wherein said decomposing, modifying and reconstructing are performed automatically upon image capture.
11. An apparatus for reducing noise in an image comprising:
memory storing said image; and
processing structure decomposing the image to generate wavelet coefficients at different scales, modifying the wavelet coefficients based on the energy of the wavelet coefficients at the different scales and reconstructing the image based on the modified wavelet coefficients;
wherein said processing structure decomposes said image into wavelet detail spaces at different scales, each wavelet detail space comprising a plurality of wavelet detail subbands and each wavelet detail subband comprising a matrix of wavelet coefficient; and
wherein during the modifying, said processing structure determines the feature energy of the wavelet coefficients according to:
FeatureEnergy
j
(
p
)
=
{
NISE
j
(
p
)
+
NeighborEnergy
j
(
p
)
j
<
J
0
SSE
j
(
p
)
+
NeighborEnergy
j
(
p
)
j
=
J
0
where NISE j (p) is the normalized inter-scale energy, SSE j (p) is the single scale energy, NeighborEnergy j (p) is the weighted average single scale energy, j is the scale and p is location (x,y) in each wavelet detail subband.
12. An apparatus according to claim 11 wherein the processing structure performs the decomposing, modifying and reconstructing independently on one or more channels of said image.
13. An apparatus according to claim 11 wherein the apparatus receives said image from an image capture device.
14. An apparatus according to claim 11 wherein the apparatus is embodied in an image capture device.
15. An apparatus according to claim 14 wherein said image capture device is a digital camera.
16. A non-transitory computer readable medium embodying a computer program for reducing noise in an image, said computer program comprising:
computer program code for decomposing the image to generate wavelet coefficients at different scales;
computer program code for modifying the wavelet coefficients based on the energy of the wavelet coefficients at different scales; and
computer program code for reconstructing the image based on the modified wavelet coefficients;
computer program code for decomposing said image into wavelet detail spaces at different scales, each wavelet detail space comprising a plurality of wavelet detail subbands and each wavelet detail subband comprising a matrix of wavelet coefficients; and
computer program code for determining the feature energy of the wavelet coefficients according to:
FeatureEnergy
j
(
p
)
=
{
NISE
j
(
p
)
+
NeighborEnergy
j
(
p
)
j
<
J
0
SSE
j
(
p
)
+
NeighborEnergy
j
(
p
)
j
=
J
0
.
where NISE j (p) is the normalized inter-scale energy, SSE j (p) is the single scale energy, NeighborEnergy j (p) is the weighted average single scale energy, j is the scale and p is location (x,y) in each wavelet detail subband.