Patent US6681054B1 successfully refreshed from Google Patents.
US6681054B1
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US
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Noise reduction method utilizing probabilistic weighting, apparatus, and program for digital image processing
Assignee: Intellectual Ventures Fund 83 LLC
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Filing: 2000-05-01
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Granted: 2004-01-20
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Expires: 2020-05-01
Abstract
Abstract A method of processing a digital image channel to remove noise, includes the steps of: identifying a pixel of interest; identifying at least two sampled local regions of pixels about the pixel of interest; calculating a noise free pixel estimate for each sampled local region of pixels; using the noise free pixel estimates, a noise model and the pixel of interest to calculate a probabilistic weighting factor for each noise free pixel estimate; and using the noise free pixel estimates and the probabilistic weighting factors for calculating a noise reduced pixel value.
Inventors
- 👤 Edward B. Gindele
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 15:48
CPC Classifications
G; G06; G06T; G06T5/00; G06T5/20; G06T5/70; G06V; G06V10/00; G06V10/20; G06V10/30; G06T2207/00; G06T2207/20; G06T2207/20076
Claims Analysis
Total Claims: 43
Claim 1
Independent Claim
107 words
A method of processing a digital image channel to remove noise, comprising the steps of: a) identifying a pixel of interest; b) identifying at least two sampled local regions of pixels about the pixel of interest; c) calculating a noise free pixel estimate for each sampled local region of pixels; d) using the noise free pixel estimates, a noise model of the expected noise level in the digital image channel and the pixel of interest to calculate a probabilistic weighting factor for each noise free pixel estimate; and e) using the noise free pixel estimates and the probabilistic weighting factors for calculating a noise reduced pixel value.
Claim 2
Independent Claim
107 words
A method of processing a digital image channel to remove noise, comprising the steps of: a) identifying a pixel of interest; b) identifying at least two sampled local regions of pixels about the pixel of interest; c) calculating a noise free pixel estimate for each sampled local region of pixels; d) using the noise free pixel estimates, a noise model of the expected noise level in the digital image channel and the pixel of interest to calculate a probabilistic weighting factor for each noise free pixel estimate; and e) using the noise free pixel estimates and the probabilistic weighting factors for calculating a noise reduced pixel value.
Claim 3
Dependent Claim
16 words
The method claimed in claim 1 , wherein the noise model is a Gaussian probability function.
Claim 4
Dependent Claim
12 words
A computer program product for performing the method of claim 2 .
Claim 5
Dependent Claim
16 words
The method claimed in claim 1 , wherein the noise model is a Laplacian probability function.
Claim 6
Dependent Claim
12 words
A computer program product for performing the method of claim 4 .
Claim 7
Dependent Claim
35 words
The method claimed in claim 1 , wherein the noise free pixel estimate is calculated as a rank order statistical value derived from the values of the pixels from the sampled local regions of pixels.
Claim 8
Dependent Claim
26 words
The method claimed in claim 6 , wherein the rank order statistical value is the statistical median of the pixel values in the sampled local region.
Claim 9
Dependent Claim
12 words
A computer program product for performing the method of claim 7 .
Claim 10
Dependent Claim
12 words
A computer program product for performing the method of claim 6 .
Claim 11
Dependent Claim
38 words
The method claimed in claim 1 , wherein the noise free pixel estimate is calculated as a function of the difference between the value of the pixel of interest and the pixel values in the sampled local region.
Claim 12
Dependent Claim
12 words
A computer program product for performing the method of claim 10 .
Claim 13
Dependent Claim
19 words
The method claimed in claim 1 , wherein one of the sampled local regions is the pixel of interest.
Claim 14
Dependent Claim
12 words
A computer program product for performing the method of claim 12 .
Claim 15
Dependent Claim
17 words
The method claimed in claim 1 , wherein the sampled local regions include the pixel of interest.
Claim 16
Dependent Claim
12 words
A computer program product for performing the method of claim 14 .
Claim 17
Dependent Claim
19 words
The method claimed in claim 1 , wherein the sampled local regions do not include the pixel of interest.
Claim 18
Dependent Claim
12 words
A computer program product for performing the method of claims 16 .
Claim 19
Dependent Claim
25 words
The method claimed in claim 1 , wherein the probabilistic weighting factor is calculated using a noise level parameter to calculate the probabilistic weighting factors.
Claim 20
Dependent Claim
12 words
A computer program product for performing the method of claim 18 .
Claim 21
Dependent Claim
22 words
The method claimed in claim 18 , wherein the noise level parameter is dependent on the value of the pixel of interest.
Claim 22
Dependent Claim
12 words
A computer program product for performing the method of claim 20 .
Claim 23
Dependent Claim
20 words
The method claimed in claim 1 , wherein steps a) through e) are repeated for all pixels in the image.
Claim 24
Dependent Claim
12 words
A computer program product for performing the method of claim 22 .
Claim 25
Dependent Claim
35 words
The method claimed in claim 1 , wherein the image includes a plurality of channels and wherein steps a) through e) are repeated for all pixels in all of the channels of the digital image.
Claim 26
Dependent Claim
12 words
A computer program product for performing the method of claim 24 .
Claim 27
Dependent Claim
23 words
The method claimed in claim 1 , wherein the sampled local regions define radial patterns of pixels emanating from the pixel of interest.
Claim 28
Dependent Claim
12 words
A computer program product for performing the method of claim 26 .
Claim 29
Dependent Claim
12 words
A computer program product for performing the method of claim 1 .
Claim 30
Dependent Claim
113 words
Apparatus for processing a digital image channel to remove noise, comprising: a) means for identifying a pixel of interest; b) means for identifying at least two sampled local regions of pixels about the pixel of interest; c) means for calculating a noise free pixel estimate for each sampled local region of pixels; d) means for using the noise free pixel estimates, a noise model of the expected noise level in the digital image channel and the pixel of interest to calculate a probabilistic weighting factor for each noise free pixel estimate; and e) means for using the noise free pixel estimates and the probabilistic weighting factors for calculating a noise reduced pixel value.
Claim 31
Dependent Claim
113 words
Apparatus for processing a digital image channel to remove noise, comprising: a) means for identifying a pixel of interest; b) means for identifying at least two sampled local regions of pixels about the pixel of interest; c) means for calculating a noise free pixel estimate for each sampled local region of pixels; d) means for using the noise free pixel estimates, a noise model of the expected noise level in the digital image channel and the pixel of interest to calculate a probabilistic weighting factor for each noise free pixel estimate; and e) means for using the noise free pixel estimates and the probabilistic weighting factors for calculating a noise reduced pixel value.
Claim 32
Dependent Claim
16 words
The apparatus claimed in claim 29 , wherein the noise model is a Gaussian probability function.
Claim 33
Dependent Claim
16 words
The apparatus claimed in claim 29 , wherein the noise model is a Laplacian probability function.
Claim 34
Dependent Claim
35 words
The apparatus claimed in claim 29 , wherein the noise free pixel estimate is calculated as a rank order statistical value derived from the values of the pixels from the sampled local regions of pixels.
Claim 35
Dependent Claim
26 words
The apparatus claimed in claim 32 , wherein the rank order statistical value is the statistical median of the pixel values in the sampled local region.
Claim 36
Dependent Claim
38 words
The apparatus claimed in claim 29 , wherein the noise free pixel estimate is calculated as a function of the difference between the value of the pixel of interest and the pixel values in the sampled local region.
Claim 37
Dependent Claim
19 words
The apparatus claimed in claim 29 , wherein one of the sampled local regions is the pixel of interest.
Claim 38
Dependent Claim
17 words
The apparatus claimed in claim 29 , wherein the sampled local regions include the pixel of interest.
Claim 39
Dependent Claim
19 words
The apparatus claimed in claim 29 , wherein the sampled local regions do not include the pixel of interest.
Claim 40
Dependent Claim
25 words
The apparatus claimed in claim 29 , wherein the probabilistic weighting factor is calculated using a noise level parameter to calculate the probabilistic weighting factors.
Claim 41
Dependent Claim
22 words
The apparatus claimed in claim 38 , wherein the noise level parameter is dependent on the value of the pixel of interest.
Claim 42
Dependent Claim
32 words
The apparatus claimed in claim 29 , wherein the image includes a plurality of channels and wherein means a) through e) are provided for each of the channels of the digital image.
Claim 43
Dependent Claim
23 words
The apparatus claimed in claim 29 , wherein the sampled local regions define radial patterns of pixels emanating from the pixel of interest.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2007-01-19 | 2007-07-21 | 2008-01-20 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2011-01-19 | 2011-07-21 | 2012-01-20 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2015-01-19 | 2015-07-21 | 2016-01-20 | $7700.00 | Window Closed / Lapsed |