US7072511B2
Expired / Lapsed
US
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Methodology for color correction with noise regulation
Assignee: Intel Corp
•
Filing: 2003-06-04
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Granted: 2006-07-04
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Expires: 2023-06-04
Abstract
Abstract A method comprising determining an optimal color correction matrix accounting for both total noise variance and color reproduction error for a captured image; and correcting the colors of said captured image using said optimal color correction matrix.
Inventors
- 👤 Yap-Peng Tan
- 👤 Tinku Acharya
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 10:40
CPC Classifications
H; H04; H04N; H04N1/00; H04N1/46; H04N1/56; H04N1/60; H04N1/603; H04N1/6033; H04N1/6016
Claims Analysis
Total Claims: 41
Claim 1
Independent Claim
59 words
A method comprising: computing an image noise level for a captured image; determining a substantially optimal color correction matrix accounting for both total noise variance and color reproduction error for the captured image, wherein the total noise variance includes the computed image noise level; and correcting the colors of said captured image using said substantially optimal color correction matrix.
Claim 2
Independent Claim
59 words
A method comprising: computing an image noise level for a captured image; determining a substantially optimal color correction matrix accounting for both total noise variance and color reproduction error for the captured image, wherein the total noise variance includes the computed image noise level; and correcting the colors of said captured image using said substantially optimal color correction matrix.
Claim 3
Dependent Claim
26 words
The method of claim 1 , wherein the substantially optimal color correction matrix has the total noise variance and the color reproduction error as primary factors.
Claim 4
Dependent Claim
38 words
The method of claim 2 , wherein accounting for both total noise variance and color reproduction error comprises a calculation including a computed value for the total noise variance and a computed value for the color reproduction error.
Claim 5
Dependent Claim
30 words
The method of claim 2 , wherein the calculating includes minimizing the value for the total noise variance and the value for the color reproduction error via a weighting factor.
Claim 6
Dependent Claim
38 words
The method of claim 1 , wherein the total noise variance comprises a calculation including a plurality of noise variances of a plurality of color channels in a plurality of respective color spaces associated with the color channels.
Claim 7
Dependent Claim
18 words
The method of claim 1 , wherein computing includes performing a matrix operation on elements of a matrix.
Claim 8
Dependent Claim
14 words
The method of claim 6 , wherein the matrix has only one single element.
Claim 9
Dependent Claim
16 words
The method of claim 6 , wherein the total noise variance is a noise covariance matrix.
Claim 10
Dependent Claim
29 words
The method of claim 1 , wherein determining includes re-determining the substantially optimal color correction matrix, if one of said total noise variance and said color reproduction error varies.
Claim 11
Dependent Claim
28 words
The method of claim 1 , wherein said determining includes: determining a preferred weighting factor that properly weights the level of color reproduction error and total noise variance.
Claim 12
Dependent Claim
32 words
The method of claim 10 , wherein determining a preferred weighting factor includes: fetching a sample image; computing a sample image pre-correction noise level; and computing a sample image pre-correction brightness level.
Claim 13
Dependent Claim
24 words
The method of claim 11 , wherein said preferred weighting factor is determined based upon said pre-correction noise level and said pre-correction brightness level.
Claim 14
Dependent Claim
35 words
The method of claim 10 , wherein generating of a substantially optimal color correction matrix includes minimizing of a cost function which inter-relates said noise variance with said color reproduction error via said weighting factor.
Claim 15
Dependent Claim
71 words
An article comprising a computer readable medium having instructions stored thereon which when executed causes: computing an image noise level for a captured image; determining a substantially optimal color correction matrix accounting for both total noise variance and color reproduction error for the captured image, wherein the total noise variance includes the computed image noise level; and correcting the colors of said captured image using said substantially optimal color correction matrix.
Claim 16
Dependent Claim
71 words
An article comprising a computer readable medium having instructions stored thereon which when executed causes: computing an image noise level for a captured image; determining a substantially optimal color correction matrix accounting for both total noise variance and color reproduction error for the captured image, wherein the total noise variance includes the computed image noise level; and correcting the colors of said captured image using said substantially optimal color correction matrix.
Claim 17
Dependent Claim
19 words
The article of claim 14 , wherein determining includes considering a color reproduction constraint upon said color correction matrix.
Claim 18
Dependent Claim
26 words
The method of claim 14 , wherein the substantially optimal color correction matrix has the total noise variance and the color reproduction error as primary factors.
Claim 19
Dependent Claim
24 words
The method of claim 14 , wherein the calculating includes minimizing the total noise variance and the color reproduction error via a weighting factor.
Claim 20
Dependent Claim
38 words
The method of claim 14 , wherein the total noise variance comprises a calculation including a plurality of noise variances of a plurality of color channels in a plurality of respective color spaces associated with the color channels.
Claim 21
Dependent Claim
29 words
The method of claim 14 , wherein determining includes re-determining the substantially optimal color correction matrix, if one of said total noise variance and said color reproduction error varies.
Claim 22
Independent Claim
88 words
A system comprising: a memory configured to store instructions and data; and a processor coupled to said memory said processor adapted to execute said instructions in conjunction with said data to cause: computing an image noise level for a captured image; determining a substantially optimal color correction matrix accounting for both total noise variance and color reproduction error for the captured image, wherein the total noise variance includes the computed image noise level; and correcting the colors of said captured image using said substantially optimal color correction matrix.
Claim 23
Independent Claim
88 words
A system comprising: a memory configured to store instructions and data; and a processor coupled to said memory said processor adapted to execute said instructions in conjunction with said data to cause: computing an image noise level for a captured image; determining a substantially optimal color correction matrix accounting for both total noise variance and color reproduction error for the captured image, wherein the total noise variance includes the computed image noise level; and correcting the colors of said captured image using said substantially optimal color correction matrix.
Claim 24
Dependent Claim
26 words
The method of claim 20 , wherein the substantially optimal color correction matrix has the total noise variance and the color reproduction error as primary factors.
Claim 25
Dependent Claim
30 words
The method of claim 20 , wherein the calculating includes minimizing the value for the total noise variance and the value for the color reproduction error via a weighting factor.
Claim 26
Dependent Claim
38 words
The method of claim 20 , wherein the total noise variance comprises a calculation including a plurality of noise variances of a plurality of color channels in a plurality of respective color spaces associated with the color channels.
Claim 27
Independent Claim
78 words
A method comprising: determining a preferred weighting factor that properly weights the level of color reproduction error and total noise variance error for a captured image; wherein said determining a preferred weighting factor includes: generating a test color correction matrix using said preferred weighting factor; applying said test color correction matrix to said captured image; and evaluating the color error and a post-correction noise level after said application of said test color correction matrix to said captured image.
Claim 28
Independent Claim
78 words
A method comprising: determining a preferred weighting factor that properly weights the level of color reproduction error and total noise variance error for a captured image; wherein said determining a preferred weighting factor includes: generating a test color correction matrix using said preferred weighting factor; applying said test color correction matrix to said captured image; and evaluating the color error and a post-correction noise level after said application of said test color correction matrix to said captured image.
Claim 29
Dependent Claim
32 words
The method of claim 24 , wherein determining a preferred weighting factor includes: fetching a sample image; computing a sample image pre-correction noise level; and computing a sample image pre-correction brightness level.
Claim 30
Dependent Claim
24 words
The method of claim 24 , wherein said preferred weighting factor is determined based upon said pre-correction noise level and said pre-correction brightness level.
Claim 31
Dependent Claim
35 words
The method of claim 24 , wherein if said color error and said post-correction noise level meet an application target, then setting the substantially optimal color correction matrix to be said test color correction matrix.
Claim 32
Dependent Claim
46 words
The method of claim 27 , wherein if said color error and said post-correction noise level do not meet an application target, then determining a new preferred weighting factor and repeating the steps of generating of a test color correction matrix, of applying and of evaluating.
Claim 33
Dependent Claim
34 words
The method of claim 24 , wherein generating of a test color correction matrix includes minimizing of a cost function which inter-relates said noise variance with said color reproduction error via said weighting factor.
Claim 34
Dependent Claim
90 words
An article comprising a computer readable medium having instructions stored thereon which when executed causes: determining a preferred weighting factor that properly weights the level of color reproduction error and total noise variance error for a captured image; wherein said determining a preferred weighting factor includes: generating a test color correction matrix using said preferred weighting factor; applying said test color correction matrix to said captured image; and evaluating the color error and a post-correction noise level after said application of said test color correction matrix to said captured image.
Claim 35
Dependent Claim
90 words
An article comprising a computer readable medium having instructions stored thereon which when executed causes: determining a preferred weighting factor that properly weights the level of color reproduction error and total noise variance error for a captured image; wherein said determining a preferred weighting factor includes: generating a test color correction matrix using said preferred weighting factor; applying said test color correction matrix to said captured image; and evaluating the color error and a post-correction noise level after said application of said test color correction matrix to said captured image.
Claim 36
Dependent Claim
35 words
The method of claim 30 , wherein if said color error and said post-correction noise level meet an application target, then setting the substantially optimal color correction matrix to be said test color correction matrix.
Claim 37
Dependent Claim
46 words
The method of claim 30 , wherein if said color error and said post-correction noise level do not meet an application target, then determining a new preferred weighting factor and repeating the steps of generating of a test color correction matrix, of applying and of evaluating.
Claim 38
Independent Claim
107 words
A system comprising: a memory configured to store instructions and data; and a processor coupled to said memory said processor adapted to execute said instructions in conjunction with said data to cause: determining a preferred weighting factor that properly weights the level of color reproduction error and total noise variance error for a captured image; wherein said determining a preferred weighting factor includes: generating a test color correction matrix using said preferred weighting factor; applying said test color correction matrix to said captured image; and evaluating the color error and a post-correction noise level after said application of said test color correction matrix to said captured image.
Claim 39
Independent Claim
107 words
A system comprising: a memory configured to store instructions and data; and a processor coupled to said memory said processor adapted to execute said instructions in conjunction with said data to cause: determining a preferred weighting factor that properly weights the level of color reproduction error and total noise variance error for a captured image; wherein said determining a preferred weighting factor includes: generating a test color correction matrix using said preferred weighting factor; applying said test color correction matrix to said captured image; and evaluating the color error and a post-correction noise level after said application of said test color correction matrix to said captured image.
Claim 40
Dependent Claim
24 words
The system of claim 33 comprising an imaging apparatus, said imaging apparatus providing said captured image, said captured image corrected on said imaging apparatus.
Claim 41
Dependent Claim
19 words
The system of claim 33 , wherein said substantially optimal color correction matrix is loaded into said imaging apparatus.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
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| 3.5 Years (Year 4) | 2009-07-03 | 2010-01-02 | 2010-07-04 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2013-07-03 | 2014-01-02 | 2014-07-04 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2017-07-03 | 2018-01-02 | 2018-07-04 | $7700.00 | Window Closed / Lapsed |