Method for color rendering using scanned halftone classification

• US 20040257619A1
• Filed: 06/17/2003
• Published: 12/23/2004
• Est. Priority Date: 06/17/2003
• Status: Active Grant

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Grzenda, Jay S., Loce, Robert P., Maltz, Martin S.
• Granted Patent: US 8,184,340 B2
• Time in Patent Office: Days
• US Class Current: 358/2.1
• CPC Class Codes: H04N 1/40075 Descreening, i.e. converting a halftone signal into a corresponding continuous-tone signal; Rescreening, i.e. combined descreening and halftoning

Abstract

What is disclosed is an image path that advantageously uses halftone classification to select appropriate mappings in gray-scale management and color management operations. The tags generated in the scanner help identify different classes of halftones. One is selected from several pixel-value mappings to provide proper compensation. That is, the one-dimensional and multi-dimensional pixel-value mappings within the color management module are selected based on halftone classification tags from the scanner. The tagging is either one bit that indicates “Low Frequency Halftone” and “Not LFHT”, or, more preferably, the tag is multi-bit indicating a frequency bin that contains the frequency of the input halftone. Additionally, the multi-bit tag can indicate particular halftone screen types, such as dot screens, line screens, stochastic screens or error diffusion. The pixel value mappings are typically implemented as Look-Up Tables (LUTs), and the LUTs of the present invention are optimized for the various halftone classes. Generation of the LUTs, or other pixel-value mappings, is non-trivial in that such mappings are normally applied to contone images and not to blurred halftoned images. The pixel-value mappings of the present invention are derived via an iterative process. Alternatively, a model for this modulated image type is used.

Claims

1. A method for obtaining a preferred color for rendering of an image containing halftoned data, comprising:

a) processing said image and generating therefrom a plurality of tags denoting the frequencies of said image'"'"'s halftoned data;

b) identifying different classes of halftones from said tags to obtain a plurality of halftone classifications;

c) selecting one of said halftone classifications; and

d) using said selected classifier, obtaining said preferred color.

2. A method for obtaining a preferred color, as in claim 1, further comprising performing spatial analysis and/or signal processing on said image to determine regions containing input halftones.

3. A method for obtaining a preferred color, as in claim 1, further comprising selecting LUTs and/or TRCs from which the preferred color is retrieved.

4. A method for obtaining a preferred color, as in claim 1, further comprising generating a set of calibration curves from said halftones.

5. A method for obtaining a preferred color, as in claim 1, wherein the tags indicate “

Low Frequency Halftone” and

“

Not LFHT”

.

6. A method for obtaining a preferred color, as in claim 1, wherein the tags indicate a frequency bin that contains the frequency of the input halftone.

7. A method for obtaining a preferred color, as in claim 1, wherein said preferred color is retrieved from LUTs and/or TRCs.

8. A method for obtaining a preferred color, as in claim 1, further comprising obtaining at least one mapping between colors observed and an output rendering of CMYK separations.

9. A method, as in claims 3 and 7, selecting LUTs and/or TRCs based on halftone classifications denoted by said tags.

10. A method, as in claims 3 and 7, selecting LUTs and/or TRCs based on screen classifiers denoted by said tags.

11. A method, as in claims 3 and 7, wherein the LUTs are a static set of tables already rendered.

12. A method, as in claims 3 and 7, wherein the LUTs have been optimized for each halftone class.

13. A method, as in claims 3 and 7, wherein the LUTs and TRCs are not binary.

14. A method, as in claims 3 and 7, wherein the LUTs are calculated dynamically via interpolation.

15. A method, as in claims 3 and 7, wherein LUTs comprise a function which has been parameterized according to the selected halftone classification.

16. A method, as in claim 2, wherein said determined regions are classified as being within certain frequency ranges, (e.g., 80-100 dpi).

17. A method, as in claim 16, wherein said frequency ranges can be large (e.g., a low-frequency halftone between 65 dpi and 150 dpi) or small (e.g., between 80 dpi and 100 dpi).

18. A method, as in claim 1, further comprising updating a color management module with the LUTs.

19. A method, as in claim 18, wherein the color management module uses halftone frequency class to apply color conversion.

20. A method, as in claim 1, further comprising generating LUTs using an iterative process based on a 16-region conceptual model of the colors input to the table.

21. A method, as in claim 20, wherein the space of scanned colors is divided into 16 regions associated with the 16 possible overprints of CMYK.

22. A method, as in claim 1, further comprising using LUTs and/or TRCs to determine a location of at least one boundary region in colorspace.

23. A method, as in claim 22, wherein an optimum boundary region in colorspace is a function of halftone frequency response.

24. A method, as in claim 22, wherein an initial estimate of any one colorspace boundary is preferred until a better estimate of that boundary location is known.

25. A system for obtaining a preferred color for rendering of an image containing halftoned data, comprising:

memory;

processing unit;

storage medium; and

program instructions performing;

a) generating a plurality of tags denoting the frequencies of said image'"'"'s halftoned data;

b) identifying different classes of halftones from said tags to obtain a plurality of halftone classifications;

c) selecting one of said halftone classifications; and

d) using said selected classifier, obtaining said preferred color from LUTs and/or TRCs.

26. A system, as in claim 25, performing spatial analysis and/or signal processing on said image to determine regions containing input halftones.

27. A system, as in claim 25, selecting LUTs and/or TRCs from which said preferred color is retrieved.

28. A system, as in claim 25, generating a set of calibration curves from said halftones.

29. A system, as in claim 25, obtaining at least one mapping between colors observed and an output rendering of CMYK separations.

30. A system, as in claim 27, wherein the LUTs and/or TRCs are selected based on halftone classifications denoted by said tags.

31. A system, as in claim 27, wherein the LUTs and/or TRCs are selected based on screen classifiers denoted by said tags.

32. A system, as in claim 25, wherein the LUTs are a static set of tables already rendered.

33. A system, as in claim 25, wherein the LUTs have been optimized for each halftone class.

34. A system, as in claim 25, wherein the LUTs and TRCs are not binary.

35. A system, as in claim 25, wherein the LUTs are calculated dynamically via interpolation.

36. A system, as in claim 25, wherein LUTs comprise a function which has been parameterized according to the selected halftone classification.

37. A system, as in claim 26, wherein said determined regions are classified as being within certain frequency ranges, (e.g., 80-100 dpi).

38. A system, as in claim 37, wherein said frequency ranges can be large (e.g., a low-frequency halftone between 65 dpi and 150 dpi) or small (e.g., between 80 dpi and 100 dpi).

39. A system, as in claim 25, further comprising a color management module in communication therewith.

40. A system, as in claim 39, updating said color management module with the LUTs.

41. A system, as in claim 39, wherein the color management module uses halftone frequency class to apply color conversion.

42. A system, as in claim 25, generating LUTs using an iterative process based on a 16-region conceptual model of the colors input to the table.

43. A system, as in claim 42, wherein the space of scanned colors is divided into 16 regions associated with the 16 possible overprints of CMYK.

44. A system, as in claim 25, further comprising using LUTs and/or TRCs to determine a location of at least one boundary region in colorspace.

45. A system, as in claim 44, wherein an optimum boundary region in colorspace is a function of halftone frequency response.

46. A system, as in claim 44, wherein an initial estimate of any one colorspace boundary is preferred until a better estimate of that boundary location is known.

47. A method for color rendering of an image with regions containing input halftones in a color management module in a print controller, comprising:

a) scanning of said image into an image processor;

b) performing spatial and/or signal processing analysis on said image to determine regions containing input halftones;

c) identifying frequencies of input halftones;

d) for each input halftone, giving a tag denoting its frequency range;

e) identifying different classes of halftones from said tags;

f) selecting one halftone classification therefrom; and

g) from said selected halftone classification, selecting a preferred color rendering from LUTs and TRCs.

48. A system for obtaining a preferred color for rendering of an image containing halftoned data, comprising:

memory;

processing unit;

storage medium; and

program instructions performing;

a) scanning of said image into an image processor;

b) performing spatial and/or signal processing analysis on said image to determine regions containing input halftones;

c) identifying frequencies of input halftones;

d) for each input halftone, giving a tag denoting its frequency range;

e) identifying different classes of halftones from said tags;

f) selecting one halftone classification therefrom; and

g) from said selected halftone classification, selecting a preferred color rendering from LUTs and TRCs.