REGISTRATION OF SEPARATIONS

• US 20130230238A1
• Filed: 03/18/2013
• Published: 09/05/2013
• Est. Priority Date: 01/04/2002
• Status: Active Grant

• Current Assignee: AOL Inc. (Apollo Global Management, Inc.), Warner Bros Entertainment Incorporated (Warner Bros. Discovery, Inc.)
• Original Assignee: AOL Inc. (Apollo Global Management, Inc.), Warner Bros Entertainment Incorporated (Warner Bros. Discovery, Inc.)
• Inventors: Perlmutter, Keren O., Perlmutter, Sharon M., Wang, Eric, Klamer, Paul R., Cookson, Christopher J., Gasparri, Massimiliano
• Granted Patent: US 8,818,088 B2
• Time in Patent Office: Days
• US Class Current: 382/164
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20064 Wavelet transform [DWT]
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 3/403 Edge-driven scaling; Edge-based scaling
• CPC Class Codes: G06T 3/4084 in the transform domain, e.g. fast Fourier transform [FFT] domain scaling
• CPC Class Codes: G06T 5/003 Deblurring; Sharpening vibration or motion blur correction for cameras comprising an electronic image sensor H04N23/682
• CPC Class Codes: G06T 5/10 using non-spatial domain filtering
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/38 Registration of image sequences
• CPC Class Codes: G06V 10/24 Aligning, centring, orientation detection or correction of the image
• CPC Class Codes: H04N 1/58 Edge or detail enhancement; Noise or error suppression, e.g. colour misregistration correction H04N1/62 takes precedence
• CPC Class Codes: H04N 23/15 Image signal generation with circuitry for avoiding or correcting image misregistration
• CPC Class Codes: H04N 5/262 Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
• CPC Class Codes: H04N 9/11 Scanning of colour motion picture films, e.g. for telecine

Abstract

Separations or images relating to film or other fields may be registered using a variety of features, such as, for example: (1) correcting one or more film distortions; (2) automatically determining a transformation to reduce a film distortion; (3) applying multiple criteria of merit to a set of features to determine a set of features to use in determining a transformation; (4) determining transformations for areas in an image or a separation in a radial order; (5) comparing areas in images or separations by weighting feature pixels differently than non-feature pixels; (6) determining distortion values for transformations by applying a partial distortion measure and/or using a spiral search configuration; (7) determining transformations by using different sets of features to determine corresponding transformation parameters in an iterative manner; and (8) applying a feathering technique to neighboring areas within an image or separation.

Claims

1. A method for automatic registration of film separations, the method comprising:

accessing component images that are based on digitized film separations, wherein each of the component images includes a set of gray-level pixels;

determining automatically an alignment vector for at least a part of a selected component image from among the accessed component images; and

correcting one or more film distortions by applying the alignment vector to the part of the selected component image.

2. The method of claim 1 wherein the accessed component images are based on digitized color film separations.

3. The method of claim 1 wherein accessing component images comprises digitizing film separations.

4. The method of claim 1 wherein the alignment vector aligns the part of the selected component image with a corresponding part of a second of the accessed component images, the method further comprising combining the selected component image and the second of the accessed component images after applying the alignment vector.

5. The method of claim 1 further comprising selecting one of the accessed component images as a reference, wherein determining the alignment vector comprises determining an alignment vector between a part of the reference and the part of the selected component image.

6. The method of claim 5 wherein a green component image is selected as the reference.

7. The method of claim 5 further comprising determining an additional alignment vector between the part of the reference and a part of an additional one of the accessed component images.

8. The method of claim 5 wherein determining the alignment vector comprises:

determining a first set of features associated with the part of the reference;

determining a second set of features associated with the part of the selected component image;

comparing the first and second sets of features based on results obtained when applying one or more candidate alignment vectors; and

determining the alignment vector based on results of the one or more comparisons.

9. The method of claim 8 wherein:

determining the first set of features comprises;

applying an edge detection filter to the part of the reference to generate a first preliminary set of edges, and

applying an edge refinement procedure to the first preliminary set of edges to obtain the first set of features; and

determining the second set of features comprises;

applying the edge detection filter to the part of the selected component image to generate a second preliminary set of edges, and

applying the edge refinement procedure to the second preliminary set of edges to obtain the second set of features.

10. The method of claim 8 wherein comparing the sets of features based on results obtained when applying one or more candidate alignment vectors comprises:

assigning a non-zero amount of distortion to a pixel in a first of the accessed component images only if the pixel is part of a feature and if a pixel at a corresponding location in a second of the accessed component images is not part of a feature; and

summing the distortion values obtained for a predefined set of pixels in an area being examined in the first component image.

11. The method of claim 10 wherein the first of the accessed component images is the selected component image.

12. The method of claim 9 wherein applying the edge refinement procedure comprises selecting edges based on a characteristic of at least one of the accessed component images.

13. The method of claim 12 wherein the characteristic comprises high intensity.

14. The method of claim 9 wherein applying the edge refinement procedure comprises:

identifying a connected edge within an area under consideration;

including the connected edge in a set of selected edges if the connected edge meets a first criterion of merit; and

obtaining a set of features based on whether the entire set of selected edges satisfies a second criterion of merit.

15. The method of claim 14 wherein:

the connected edge meets the first criterion of merit if the connected edge has at least a predetermined amount of information in one direction, and

the set of selected edges satisfies the second criterion of merit if the entire set of selected edges has at least a predetermined amount of information.

16. The method of claim 8 wherein comparing the sets of features based on results obtained when applying one or more candidate alignment vectors comprises:

selecting an initial candidate alignment vector; and

varying the initial candidate alignment vector so as to represent multiple relative displacement possibilities within a particular proximity window of the initial candidate alignment vector.

17. The method of claim 16 wherein selecting the initial candidate alignment vector comprises:

determining a first set of features associated with a center part of the reference;

determining a second set of features associated with a center part of the selected component image;

comparing the first and second sets of features associated with the center parts of the reference and the selected component image; and

selecting the initial candidate alignment vector based on results of the comparison of the center portions.

18. The method of claim 8 wherein determining the alignment vector comprises:

dividing the selected component image into a set of areas;

determining an initial alignment vector for a particular area based on at least one previously determined alignment vector for another area; and

determining the alignment vector for the particular area based on the initial alignment vector for the particular area

19. A computer program for automatic registration of film separations, the computer program residing on a computer-readable medium and comprising instructions for causing a computer to perform operations including:

accessing component images that are based on digitized film separations, wherein each of the component images includes a set of gray-level pixels;

determining automatically an alignment vector for at least a part of a selected component image from among the accessed component images; and

correcting one or more film distortions by applying the alignment vector to the part of the selected component image.

20. An apparatus for automatic registration of film separations, the apparatus comprising one or more processors programmed to perform at least the following operations:

accessing component images that are based on digitized film separations, wherein each of the component images includes a set of gray-level pixels,

determining automatically an alignment vector for at least a part of a selected component image from among the accessed component images, and

correcting one or more film distortions by applying the alignment vector to the part of the selected component image.