Source: http://www.google.com/patents/US7835570?dq=6,249,7726,249,772
Timestamp: 2014-12-28 17:47:56
Document Index: 115414754

Matched Legal Cases: ['Application No. 60', 'Application No. 2003', 'art1', 'art 2', 'art2', 'art1', 'art1', 'art1', 'art 2', 'art2', 'art1', 'art1']

Patent US7835570 - Reducing differential resolution of separations - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsCertain disclosed implementations use digital image processing to reduce the differential resolution among separations or images in film frames, such as, for example, red flare. A location in the red image may be selected using information from another image. The selected location may be modified using...http://www.google.com/patents/US7835570?utm_source=gb-gplus-sharePatent US7835570 - Reducing differential resolution of separationsAdvanced Patent SearchPublication numberUS7835570 B1Publication typeGrantApplication numberUS 11/608,556Publication dateNov 16, 2010Filing dateDec 8, 2006Priority dateJan 4, 2002Fee statusPaidAlso published asUS7218793, US20060034541, WO2004059574A2, WO2004059574A3Publication number11608556, 608556, US 7835570 B1, US 7835570B1, US-B1-7835570, US7835570 B1, US7835570B1InventorsKeren O. Perlmutter, Sharon M. Perlmutter, Eric Wang, Paul R. KlamerOriginal AssigneeWarner Bros. Entertainment Inc., Aol Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (76), Non-Patent Citations (29), Classifications (25), Legal Events (2) External Links: USPTO, USPTO Assignment, EspacenetReducing differential resolution of separationsUS 7835570 B1Abstract Certain disclosed implementations use digital image processing to reduce the differential resolution among separations or images in film frames, such as, for example, red flare. A location in the red image may be selected using information from another image. The selected location may be modified using information from that other image. The selection may include comparing features of an edge in the first image with features of a corresponding edge in the other image. The modification may include performing wavelet transformations of the two images and copying certain coefficients (or a function of these coefficients) produced by the application of the transformation to the second image to the coefficients produced by the application of the transformation to the first image. The copied coefficients may be correlated with the selected location. Other disclosed techniques vary from the above and may be applied to other fields.
3. The method of claim 1 wherein the first region and the second region are derived from a common sub-portion of the composite color image.
4. The method of claim 1 wherein the first image and the second image populate to a common sub-portion of screen real estate on a display upon which the screen is displayed.
determining, based on the first image, a property for the first region within the first image;
determining, based on the second image, the property for the second region within the second image and that corresponds to the first region; and
modifying the property determined for the second region based on the property determined for the first region.
determining the property for the first and second regions comprises determining a property that characterizes pixels in the first and second regions, respectively.
7. The method of claim 6 further comprising modifying pixels in the second region based on the property determined for the first region.
8. The method of claim 5 wherein modifying the property determined for the second region comprises setting the property determined for the second region equal to a function of the property determined for the first region.
9. The method of claim 5 wherein determining the property for the second region comprises determining a frequency-based property for the second region.
10. The method of claim 9 wherein determining the frequency-based property comprises determining a coefficient of a transformation, into a frequency domain representation, of at least a portion of the second region.
11. The method of claim 10 wherein determining the coefficient of the transformation comprises determining a coefficient of a wavelet transformation of at least the portion of the second region.
12. The method of claim 11 wherein modifying the property determined for the second region comprises replacing the determined coefficient of the wavelet transformation of at least the portion of the second region with a function of a coefficient of a wavelet transformation of at least a portion of the first region.
13. The method of claim 12 wherein replacing the determined coefficient comprises replacing the determined coefficient with a scaled value of the coefficient of the wavelet transformation of at least the portion of the first region.
14. The method of claim 5 wherein determining the property for the second region comprises:
identifying a feature that is in the portion of the scene; and
determining measurable criteria related to the feature in the second image.
the feature comprises an edge, and identifying the feature comprises identifying the edge, and the measurable criteria comprise spectral information, and determining the measurable criteria comprises determining spectral information for the edge.
16. The method of claim 15 wherein the spectral information corresponds to red coloration in the portion of the scene, and modifying the property determined for the second region comprises modifying the spectral information corresponding to red coloration in the portion of the scene, thereby reducing red fringing of the edge.
18. The method of claim 17 further comprising selecting one or more data elements of the second set of data, and wherein modifying the property determined for the second region based on the property determined for the first region comprises setting each of the selected one or more data elements of the second set of data equal to a function of the corresponding data elements of the first set of data.
22. The method of claim 5 wherein accessing the first image comprises accessing a red separation that was extracted from a composite color image.
23. The method of claim 5 wherein the first region and the second region are derived from a common sub-portion of the composite color image.
24. The method of claim 5 wherein the first image and the second image populate to a common sub-portion of screen real estate on a display upon which the screen is displayed.
25. An apparatus comprising a computer readable medium that includes instructions for performing at least the following:
26. An apparatus comprising a computer readable medium that includes instructions for performing at least the following:
CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority from and is a continuation of U.S. application Ser. No. 11/206,182, filed Aug. 18, 2005, now U.S. Pat. No. 7,218,793, and titled �Reducing Differential Resolution of Separations,� which is a continuation of (1) U.S. application Ser. No. 10/657,243, filed Sep. 9, 2003, now U.S. Pat. No. 6,947,607, and titled �Reduction of Differential Resolution of Separations,� and (2) U.S. application Ser. No. 10/657,138, filed Sep. 9, 2003, now U.S. Pat. No. 6,956,976, and titled �Reduction of Differential Resolution of Separations,� both of which claim priority from and are continuations-in-part of U.S. application Ser. No. 10/035,337, filed Jan. 4, 2002, now U.S. Pat. No. 7,092,584, and titled �Registration of Separations,� and claim priority from U.S. Provisional Application No. 60/434,650, filed Dec. 20, 2002, and titled �Reduction of Differential Resolution of Separations.� All of the above-identified applications are incorporated herein by reference in their entirety.
DESCRIPTION OF DRAWINGS FIG. 1A is an image in which red fringing is manifested from differential resolution of separations.
(x,y), where 0<=x<=width, and 0<=y<=height.
I(x,y), where 0<=I(x,y)<=I_max.
In FIG. 5, edge pixels occur at locations (1,3) to (3,3), locations (5,1) to (9,1), locations (3,8) to (4,8), and locations (7,6) to (8,6). Assuming that a distance of two pixels is acceptable, and that any other matching criteria are satisfied for the edge pixels at locations (1,3), (2,3), (3,3), (5, 1), (6,1), (7,1) and (8,1) when compared to edge pixels (1,4) (2,4), (3,4), (5,3), (6,3), (7,3), and (8,3), respectively, in edge map 600, then these edge pixels are labeled as M pixels. The edge pixel at location (9,1) in edge map 500 is assumed, for purposes of illustration, to be a potential match to edge pixel (9,3) in edge map 600. The edge pixels at locations (3,8) and (4,8) are assumed not to match any edge pixels in edge map 600. The edge pixels at locations (7,6) and (8,6) are assumed, for purposes of illustration, to be a potential match for edge pixels in edge map 600.
Process 1400 includes modifying the coefficients in the locations determined above (1440). In one implementation, the coefficients are modified by being replaced.
In particular, the coefficients from the determined locations in the result produced by the application of the wavelet transformation to the reference digital image are copied (or scaled values are copied) over the coefficients in the determined locations in the result produced by the application of the wavelet transformation to the red digital image. Thus, the resolution information (or a function of the resolution information) for the reference digital image replaces the resolution information for the red digital image in the determined coefficient locations. Scaling a coefficient refers to multiplying the coefficient by a particular number.
The sizes of the feather extents typically impact the rate at which the intensity values for the pixels at the boundaries blend from one value to another. Various techniques may be used to determine the size of the extents for each row or column corresponding to an NM/M (or Ref1/Ref2) pixel transition. In one implementation, the sizes of the feather extents are determined based on the intensity values of R, G, and B as well as the intensity values of the modified red image, M1 R. For example, assuming that M1 R (i,j) is the red intensity value for the NM pixel at the NM/M transition after the red image has been processed by the modification unit, and M1 R(i,j+1) is the red intensity value for the M pixel at the NM/M transition after the red image has been processed by the modification unit, a value diff may be defined as:
where constant >=0, but typically is less than 1.
FIG. 16 provides a simplified example involving a portion of a single column, i. In FIG. 16, pixel (i,j) is an NM pixel and (i,j+1) is an M pixel. M1 R (i,j)=130, M1 R (i,j+1)=90, and diff=40. Also, assume diff2 is 1. Assuming �constant� has a value of 0.1, then E1=4 which includes M1 R (i,j+1) through M1 R (i,j+4).
The extent may be further refined based on the similarity of the adjacent pixel intensities with the same designations. In one implementation, continuing the above example, given an M pixel at location (i, j+1) and an extent E1, the following operations are performed for pixels (i, k), for j+1≦k≦=j+E1, where k is an integer:
The above algorithm can be applied to the column shown in FIG. 16. In the first pass through the algorithm, k=j+2. In operation 1, pixel (i,j+2) is compared to pixel (i,j+1), and both are M pixels. In operation 2b, the (R,G,B) intensity values of pixel (i,j+2) are compared to the (R,G,B) intensity values of pixel (i,j+1). The comparison may be, for example, to determine the absolute value of a difference for each color component, in which case, the comparison yields a result of (3,3,2) (that is, 128-125, 127-130, 118-116). In operation 3, the result of (3,3,2) is checked to determine if a metric is satisfied. The metric may be, for example, a maximum acceptable difference for each component, and the value of the maximum acceptable difference may be, for example, 6. In such an implementation, the metric is satisfied because the differences for each color component, that is, 3, 3, and 2, are less than the maximum acceptable difference of 6.
In the second pass through the algorithm, k=j+3. In operation 1, pixel (i,j+3) is compared to pixel (i,j+2), and both are M pixels. In operation 2b, assuming the comparison is the absolute difference in intensity values, the comparison yields a result of 7 (125-118) for the R component and 1 for both the G and B components. In operation 3, assuming the metric is a maximum difference of 5, the result of 7 fails to satisfy the metric. In operation 4, the extent is defined as pixels (i,j+1) and (i,j+2), which is smaller than the earlier determined extent of 4.
The feather extent can be extended across both M and NM pixel locations, across only M pixel locations, or across only NM pixel locations (or, analogously, across both Ref1 and Ref2 pixel locations, across only Ref1 pixel locations, or across only Ref1 pixel locations in the case where there is an Ref1/Ref2 boundary transition). If the feather extent is extended across the NM pixel locations as well as the M pixels, an analogous procedure to the operations described above, for example, may be applied to the NM pixels near the NM/M transition boundary.
Additionally, the reference digital image need not be fixed for a given image (frame). For example, the reference digital image may vary depending on the edge or pixel being considered. Further, if it is determined that a particular edge in the lower resolution image contains a matching edge in more than one of the other digital images, then the reference digital image may be iterated through the two possibilities in multiple passes through classification unit 330 to determine which digital image, or the combination, is a more preferred reference. In one implementation, a set of connected edge pixels always use the same reference digital image. This reference digital image may be determined based on which reference digital image each of the edge pixels selected, that is, the reference digital image selected by the majority of the edge pixels. In these examples in which more than one reference digital image can be used within a given image, the classification unit 320 also may specify which one or more of the reference digital images are to provide the information that will be used to modify the selected portions of the lower resolution image. The specification of the reference digital image(s) and the identification of the selected portions to which a given reference digital image applies may be provided in the classification map, as discussed earlier, or elsewhere.
Referring again to modification unit 340, the resolution content of the images may be modified using time domain analysis, frequency domain analysis, and/or wavelet domain analysis. The implementation described above uses wavelet transformations and may limit the extent of the resolution modifications by ensuring in the time domain that no NM pixels are modified. Other transformations may be used, particularly transformations for which the frequency or resolution information is correlated with spatial or time information, such as, for example, the short-term Fourier transform. Further, different types of transformations may be used within a given implementation.
Additionally, temporally-based methods, such as, for example, frame-to-frame analysis, which was mentioned above in the context of classification, may be used to modify an image (frame). Such frame-to-frame analysis may include, for example, many of the techniques already described.
Implementations and features may be implemented in a process, a device, or a combination of devices. Such a device may include, for example, a computer or other processing device capable of processing instructions using, for example, a processor, a programmable logic device, an application specific integrated circuit, or a controller chip.
Instructions may be in the format of, for example, software or firmware. Instructions may be stored in a computer readable medium, such as, for example, a disk, a random-access memory, or a read-only memory.
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