Sharpening a halftoned image

• US 7,719,719 B2
• Filed: 09/18/2006
• Issued: 05/18/2010
• Est. Priority Date: 09/18/2006
• Status: Expired due to Fees

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Zhang, Yeqing, Loce, Robert P., Xu, Beilei
• Primary Examiner(s): Popovici; Dov
• Application Number:
  US11/522,610
• Publication Number:
  US 20080068660A1
• Time in Patent Office: 1,338 Days
• Field of Search: 358/3.06, 358/1.9, 358/1.1, 358/1.2, 358/2.1, 358/3.01, 358/3.02, 358/3.03, 358/3.04, 358/3.05, 358/3.07, 358/3.08, 358/3.09, 358/3.1, 358/3.11, 358/3.12, 358/3.13, 358/3.14, 358/3.15, 358/3.2, 358/3.26, 358/3.27, 358/3.3, 358/1.11, 358/1.18, 358/1.15, 358/534, 358/535, 358/536, 382/254, 382/255, 382/266, 382/267, 382/268, 382/269, 382/264, 345/596, 345/611, 345/616, 345/617, 345/89, 347/131, 399/180, 399/181
• US Class Current: 358/3.06
• 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
• CPC Class Codes: H04N 1/4092 Edge or detail enhancement

Abstract

Images that include halftone structures are sharpened. A copy of received halftone image data is blurred, thereby reducing a detectability of edges of the halftone structures. Edges remaining in the blurred image data are detected. An edge enhancement image is generated based on the detected edges. The original received halftone image data is combined with the edge enhancement image, thereby generating sharpness enhanced image data having halftone structures. The sharpness enhanced image data having halftone structures can be rendered through a halftone screen that is compatible with a halftone screen that was used to generate the originally received image data. Alternatively, the sharpness enhanced image data having halftone structures is rendered according to error diffusion techniques, such as, rank order error diffusion in order to achieve or maintain dot or halftone structure compaction.

Claims

1. A method for producing sharpness enhanced image data having halftone structures based on input image data that includes halftone structures, the method comprising:

receiving the image data that includes halftone structures;

blurring a copy of the image data, thereby generating blurred image data wherein a detectability of edges of the halftone structures is reduced from the detectability of the edges of the halftone structures in the received image data;

detecting detectable edges remaining in the blurred image data;

generating an edge enhancement image based on the detected edges; and

combining the received image data that includes halftone structures with the generated edge enhancement image, thereby generating sharpness enhanced image data having halftone structures.

2. The method of claim 1 wherein at least a portion of the blurring occurs as an aspect of a scanning process used to generate the copy of the image data.

3. The method of claim 1 wherein at least a portion of the blurring occurs as an aspect of applying a Canny edge detector to the copy of the image data.

4. The method of claim 1 wherein at least a portion of the blurring occurs as an aspect of applying a filtering kernel to the copy of the image data.

5. The method of claim 4 wherein applying a filtering kernel to the copy of the image data comprises:

applying at least one of;

a Gaussian blurring kernel, a triangular blurring kernel, a rectangular blurring kernel, and a sinc² blurring kernel to the copy of the image data.

6. The method of claim 4 wherein a recognized width of the kernel is one of:

at least as large as a local halftone periodicity of the copy of the image data, at least as large as a halftone cell dimension of the received image data, from about one to about four times the halftone cell dimension of the received image data.

7. The method of claim 1 wherein detecting edges comprises:

enhancing ahe contrast of the blurred image data, thereby generating contrast enhanced image data; and

detecting detectable edges in the contrast enhanced image data.

8. The method of claim 7 wherein detecting edges comprises:

applying a Canny edge detection algorithm to the contrast enhanced image data.

9. The method of claim 8 wherein combining the received image data with the generated edge enhancement image comprises:

one of;

adding, subtracting, selecting a maximum of, and selecting a minimum of respective pixel values of the edge enhancement image to, from or and, respective pixel values of the received image data.

10. The method of claim 9 further comprising:

applying a form of error diffusion to the sharpness enhanced image data having halftone structures, thereby generating marking decisions for the sharpness enhanced image data having halftone structures.

11. The method of claim 10 wherein applying a form of error diffusion comprises:

applying a form of rank order error diffusion to the sharpness enhanced image data having halftone structures.

12. The method of claim 9 further comprising:

applying a halftone screen having frequency components that are harmonically compatible with respective frequency components of a halftone screen used to generate the received image data to the sharpness enhanced image data having halftone structures, thereby generating marking decisions for the sharpness enhanced image data having halftone structures.

13. The method of claim 1 wherein combining the received image data with the generated edge enhancement image comprises:

one of;

logically ANDing, logically ORing, logically exclusive ORing, respective pixel values of the edge enhancement image, with respective pixel values of the received image data, thereby generating the sharpness enhanced image data having halftone structures as marking decisions.

14. An image processor that is operative to produce sharpness enhanced image data having halftone structures based on input image data that includes halftone structures, the image processor comprising:

an image receiver that is operative to receive the image data that includes halftone structures;

a blurring mechanism that is operative to blur a copy of the received image data, thereby generating blurred image data wherein a detectability of edges of the halftone structures is reduced from the detectability of the edges of the halftone structures in the received image data;

an edge detector that is operative to detect detectable edges remaining in the blurred image data;

an enhancement image generator that is operative to generate an edge enhancement image based on the edges detected by the edge detector; and

an image combiner that is operative to combine the received image data that includes halftone structure with the generated edge enhancement image, thereby generating sharpness enhanced image data having halftone structures.

15. The image processor of claim 14 wherein the image receiver and the blurring mechanism comprise:

an image scanner that is operative to receive the image data in a form of a halftone image printed on print media, scan the print media at a scanner resolution and/or scanner alignment that is different from a screen frequency and/or screen alignment used in printing the halftone image, thereby generating scanned image data wherein the detectability of edges of the halftone structures is reduced from the detectability of the edges of the halftone structures in the printed halftoned image and whereby the scanned image data comprises the blurred image data.

16. The image processor of claim 14 wherein the blurring mechanism is operative to blur the received image data by applying at least one of:

a Gaussian blurring kernel, a triangular blurring kernel, a rectangular blurring kernel, and a sinc² blurring kernel to the copy of the image data.

17. The image processor of claim 16 wherein a recognized width of the kernel is one of:

at least as large as a local halftone periodicity of the copy of the image data, at least as large as a halftone cell dimension of the received image data, from about one to about four times the halftone cell dimension of the received image data.

18. The image processor of claim 14 wherein the edge detector is operative to detect edges by enhancing a contrast of the blurred image data, thereby generating contrast enhanced image data and detecting detectable edges in the contrast enhanced image data.

19. The image processor of claim 18 wherein the edge detector is operative to detect edges by applying a Canny edged detection algorithm to the contrast enhanced image data.

20. The image processor of claim 14 wherein the image combiner is operative to combine the received image data with the generated edge enhancement image by one of:

adding, subtracting, selecting a maximum of, and selecting a minimum of respective pixel values of the edge enhancement image to, from or and, respective pixel values of the received image data.

21. The image processor of claim 20 further comprising:

a rendering module that is operative to apply a form of error diffusion to the sharpness enhanced image data having halftone structures, thereby generating marking decisions for the sharpness enhanced image data having halftone structures.

22. The image processor of claim 21 wherein the rendering module is operative to apply a form of rank order error diffusion to the sharpness enhanced image data having halftone structures, thereby generating marking decisions for the sharpness enhanced image data having halftone structures.

23. The image processor of claim 20 further comprising:

a rendering module that is operative to apply a halftone screen having frequency components that are harmonically compatible with respective frequency components of a halftone screen used to generate the received image to the sharpness enhanced image data having halftone structures, thereby generating marking decisions for the sharpness enhanced image data having halftone structures.

24. The image processor of claim 14 wherein the image combiner is operative to combine the received image data with the generated edge enhancement image by one of:

logically ANDing, logically ORing, logically exclusive ORing, respective pixel values of the edge enhancement image, with respective pixel values of the received image data, thereby generating the sharpness enhanced image data having halftone structures as marking decisions.

25. The image processor of claim 14 further comprising at least one xerographic or ink jet based image output device that is operative to print a representation of the sharpness enhanced image data having halftone structures based on marking decisions generated from the sharpness enhanced image data having halftone structures.

26. A method for enhancing a sharpness of image data that includes halftone structures, the method comprising:

receiving the image data that includes halftone structures;

blurring the received image data, thereby generating blurred image data wherein a detectability of edges of the halftone structures is reduced from the detectability of the edges of the halftone structures in the received image data;

detecting detectable edges remaining in the blurred image data;

generating an edge enhancement image based on the detected edges; and

combining the received image data that includes halftone structure with the generated edge enhancement image, thereby generating sharpness enhanced image data having halftone structures; and

applying one of;

halftone screening with at least one screen that is harmonically compatible with a screen used in generating the received image data, and rank order error diffusion to the sharpness enhanced image data having halftone structures, thereby rendering the image data as marking decisions for printing a representation of the sharpness enhanced image data having halftone structures.