Ising-model image rendition, and consolidated masking and/or filtering, in incremental printing

• US 20060164688A1
• Filed: 01/26/2005
• Published: 07/27/2006
• Est. Priority Date: 01/26/2005
• Status: Active Grant

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Garcia, Joan-Manel, Manuel de Pena, Alejandro, Garcia-Reyero, Santiago
• Granted Patent: US 8,233,194 B2
• Time in Patent Office: Days
• US Class Current: 358/3.30
• CPC Class Codes: G06K 15/107 Mask selection
• CPC Class Codes: H04N 1/405 Halftoning, i.e. converting the picture signal of a continuous-tone original into a corresponding signal showing only two levels

Abstract

One aspect of the method/apparatus finds, for each input-image pixel, an “offset weighted average” of neighboring-pixel interactions—and uses the averages to make a final image. Another aspect assumes a value for each pixel, to use in a final rendered image form—and, at each in a series of approximations, determines whether to change the value, and finds a probabilistic weight to help determine. Yet another finds, for each pixel, a numerical representation of neighboring-pixel interactions—and establishes a distance cutoff for use in defining “neighbor”, and uses the representation to decide whether to change color values. Still another finds a desired or ideal number of print passes, and adapts the number of passes actually used to the found number. Another combines halftoning and printmasking into one procedure and prints images prepared thereby. Another integrates halftoning and image filtering, to obtain esthetic visual effects, into one procedure—and prints images thus prepared.

Claims

1. An image-processing method, for use in printing based on a digital-array representation of an input image;

said method comprising the steps of;

for substantially each particular pixel in the digital array, calculating an offset weighted average of neighboring-pixel interactions with the particular pixel; and

using the offset weighted averages to develop a final processed form of the image.

2. The method of claim 1, wherein:

the using step comprises determining changes in the averages, at substantially each stage in a series of successive approximations to the final processed form of the image.

3. The method of claim 2, wherein:

the using step further comprises applying the changes to decide whether a value for the particular pixel, at a particular stage, should be modified in said particular stage to a different value in the next stage.

4. The method of claim 3, wherein:

the using step comprises calculating a probabilistic weight for use in determining whether to perform a modification of the assumed value of the particular pixel.

5. The method of claim 4, wherein:

the using step further comprises applying a randomly selected discriminator to modulate the calculated probabilistic weight, in determining whether or not to actually modify the assumed value.

6. The method of claim 4, wherein:

the modification is a level flip.

7. The method of claim 2, further comprising the step of:

finding the final processed form of the image, through convergence of a multiplicity of said successive approximations.

8. The method of claim 1, wherein:

the calculating step comprises finding each offset weighted average as

$\frac{S_{\mathrm{jk}}+i_j}{S_k+l}$

where;

S_k represents the sum of products of the assumed value for the particular pixel j with weighted influences by neighboring pixels k,

i_j represents possible values for a particular pixel j, and

S_k represents the sum of said influences of the neighboring pixels k.

9. The method of claim 8, wherein:

each weighted average is offset from a simple weighted average by the terms +i_j and +1, in numerator and denominator respectively.

10. The method of claim 8, wherein:

for a binary-value system, a particular binary value selected for the term +i_j depends upon algebraic sign of the value i_j; and

for a multiple-discrete-value system, a particular discrete value selected for the term +i_j depends upon a digital resolution, within the available multiple values, of the value i_j.

11. The method of claim 1, wherein:

each particular pixel in the digital array is selected in turn, for performance of the calculating and using steps, by random walk thru the array.

12. The method of claim 1, wherein the calculating, determining and using steps, considered in the aggregate, comprise:

defining discrete levels and the error, if any, between each of them and the true contone level at each pixel;

but

no explicit distribution of error from each pixel, after its calculation, to neighboring pixels.

13. The method of claim 12, wherein:

said discrete levels are two binary levels.

14. The method of claim 12, wherein:

said discrete levels are multiple levels.

15. The method of claim 1, wherein:

the image processing comprises image rendering in preparation for incremental printing.

16. The method of claim 1, wherein:

the image processing comprises printmasking in preparation for incremental printing.

17. An image-rendering method, for use in printing based on a digital-array representation of an input image;

said method comprising the steps of;

for substantially each particular pixel in the digital array, assuming or establishing a specific discrete value for use in a final rendered form of the image;

at substantially each stage in a series of successive approximations to a final rendered form of the image, determining whether to change each discrete value to a different discrete value; and

for substantially each stage, calculating a probabilistic weight for substantially each pixel, to use in the determining step.

18. The method of claim 17, for use particularly in incremental printing from said digital representation that numerically approximates a substantially continuous-tone input image;

and wherein;

the calculated probabilistic weights in the aggregate operate to drive the overall array of values toward a final form that visually approximates the continuous-tone input image.

19. The method of claim 17, wherein:

the discrete values are arrayed on a scale which is at least eight times more granular than that of the digital input array.

20. The method of claim 17:

wherein the series comprises a multiplicity of the successive approximations; and

further comprising the step of finding the final rendered form of the image through convergence of the multiplicity of successive approximations.

21. The method of claim 20, wherein:

the multiplicity is between three and six, inclusive, successive approximations.

22. The method of claim 17, further comprising the step of:

applying a randomly selected discriminator to perturb the calculated probabilistic weight, in determining whether or not to actually perform a particular value change.

23. The method of claim 17, wherein:

each particular pixel in the digital array is selected in turn by random walk thru the array, for said assuming or establishing, determining, and calculating steps.

24. The method of claim 17, wherein:

the method comprises no explicit distribution of error in the rendered value of a pixel, after its calculation, to neighboring pixels.

25. The method of claim 17, further comprising the step of:

applying a randomly selected discriminator to perturb the calculated probabilistic weight, in determining whether or not to actually perform a particular value change.

26-32. -32. (canceled)

33. An image-processing method, for use in printing based on a digital-array representation of an input image;

said method comprising the steps of;

for each of plural regions of the input image, respectively, determining a number of printing passes that is desired or ideal; and

adapting the number of printing passes actually used, in at least some plural regions of the image, to the determined number.

34. An image-processing method, for use in printing based on a digital-array representation of an input image;

said method comprising the steps of;

combining matrix-based halftoning and printmasking into an integrated procedure; and

printing the image with the image halftoned and printmasked by said integrated procedure.

35. The method of claim 34, wherein:

the integrated procedure comprises a single step that effects both halftoning and printmasking.

36. The method of claim 34, wherein:

the halftoning mask is quantized into as many receptacles as the maximum number of passes required or desired.

37. The method of claim 36, wherein:

the receptacles are not all the same size.

38. The method of claim 34, wherein:

the number of passes used in at least some of plural regions in the image is adapted to the maximum number of passes required or desired in said regions, respectively.

39. The method of claim 38, wherein:

in at least some of the plural regions, unneeded passes are skipped.

40. The method of claim 38, wherein:

in at least one particular region, passes that are available by reason of required or desired passes in a nearby region are used even though not required in said particular region.

41. The method of claim 34, wherein:

the integrated procedure determines, for each element of said array, whether or not to print in each pass.

42. An image-processing method, for use in printing based on a digital-array representation of an input image;

said method comprising the steps of;

combining halftoning and image filtering, to obtain esthetic visual effects, into an integrated procedure; and

printing the image with the image halftoned and filtered by said integrated procedure.

43. The method of claim 42, wherein:

the integrated procedure is performed substantially by an Ising-model process, in which convolution weights are assigned to perform both the halftoning and filtering substantially simultaneously.