Methods and Systems for Scanning and Processing an Image Using the Error Diffusion Screening Technology

• US 20090296165A1
• Filed: 08/22/2007
• Published: 12/03/2009
• Est. Priority Date: 08/22/2006
• Status: Active Grant

• Current Assignee: New Founder Holdings Development Limited Liability Company, Beijing Founder Electronics Company Limited (Peking University), Peking University
• Original Assignee: Peking University Founder Group Company Limited (Beijing Peking University Asset Management Company Limited)
• Inventors: Yang, Bin, Li, Haifeng
• Granted Patent: US 8,411,310 B2
• Time in Patent Office: Days
• US Class Current: 358/448
• CPC Class Codes: H04N 1/4052 by error diffusion, i.e. transferring the binarising error to neighbouring dot decisions

Abstract

Disclosed is a method for scanning and processing an image using the error diffusion screening technology, comprising: (1) scanning each pixel M_i of an n^th line in an original image one by one and then storing a scanning result of the pixel M_i to an i^th storage location; and (2) processing the stored result of the pixel M_i by using error diffusion and scanning pixels of an n+1^th line in the original image until all pixels of the n^th line have been processed and all pixels in the n+1^th line have been scanned and stored, wherein once processing for the pixel M_i is completed, a scanning result of a pixel of the n+1^th line is stored to the i^th storage location previously occupied by the pixel M_i. Based on the method, the capacity for storing is only required to be able to store the data of one line in an image in the scanning direction, which saves the storage for bidirectional scanning. The method can optimize the hardware used to implement error diffusion and improve the operating efficiency. Also disclosed is a system for achieving the method.

Claims

1. A method for scanning and processing an image using the error diffusion screening technology, comprising:

(1) scanning each pixel M_i of an n^th line in an original image one by one and then storing a scanning result of the pixel M_i to an i^th storage location; and

(2) processing the stored result of the pixel M_i by using error diffusion and scanning pixels of an n+1^th line in the original image until all pixels of the n^th line have been processed and all pixels in the n+1^th line have been scanned and stored,

wherein once processing for the pixel M_i is completed, a scanning result of a pixel of the n+1^th line is stored to the i^th storage location previously occupied by the pixel M_i.

2. The method of claim 1, wherein the step (2) further comprises:

recording a processing direction parameter C of the n^th line and a storing location parameter H for a beginning pixel of the n+1^th line; and

determining the processing direction of the n+1^th line based on values of the parameters C and H.

3. The method of claim 2, wherein C=0 indicates that pixels in the n^th line are processed from beginning to end;

C=1 indicates that pixels in the n^th line are processed from end to beginning;

H=0 indicates that the beginning pixel of the n+1^th line is stored in a first location of a storing device; and

H=1 indicates that the beginning pixel of the n+1^th line is stored in a last location of the storing device.

4. The method of claim 3, wherein the processing direction is determined by the parameters C and H according to following conditions:

(1) If C=0 and H=0, pixels in the n+1^th line are processed by a processing device from the last location of a storing device;

(2) If C=0 and H=1, the pixels in the n+1^th line are processed by the processing device from the first location of the storing device;

(3) If C=1 and H=0, the pixels in the n+1^th line are processed by the processing device from the first location of the storing devices;

(4) If C=1 and H=1, the pixels in the n+1^th line are processed by the processing device from the last location of the storing device.

5. The method of claim 1, wherein the error diffusion further comprises:

(a) scanning and inputting the original image, carrying out an operation of a threshold comparison on a final value g″

(m, t) of a current pixel in the original image, and then converting a result of the operation to an output value b(m, t) of the current pixel;

(b) comparing the output value b(m, t) of the current pixel with a medium value g′

(m, t) of the current pixel to obtain an error value e(m, t) of the current pixel;

(c) multiplying the error value e(m, t) by preset weight distribution coefficients through a first diffusion filter e and then diffusing results of the multiplying to unprocessed pixels around the current pixel, wherein each of the diffused results to the unprocessed pixels around the current pixel is weightedly added to an original value g(m, t) of the pixel M, to obtain a new medium value g′

(m, t) of the pixel M_x;

(d) diffusing processed results to corresponding pixels M_x surrounding the current pixel, respectively, and weightedly adding each of the diffused processed results to the medium value g′

(m, t) of the corresponding pixel M_x obtained from error diffusion in the step (c) to obtain the final value g″

(m, t) of the corresponding pixel M_x, wherein the processed results are obtained by implementing a multiplying operation on the output value b(m, t) of the current pixel using a second diffusion filter w and processing results of the multiplying operation with a dithering algorithm, and the step (d) is implemented in parallel with the steps (b) and (c); and

(e) repeating the steps (a)-(d) until the original input values g(m, t) of all pixels are processed.

6. The method of claim 5, wherein the first error diffusion filter e in the step (c) uses a diffusion principle and weight distribution coefficients as below:

7. The method of claim 6, wherein a diffusion mode of the second diffusion filter w is set as:

8. The method of claim 7, wherein the dithering algorithm for the second diffusion filter w in the step (d) is as below:

fRand=(R(m,t)/R_MAX−

0.5)×

cDither

dw₀=w₀−

fRand

dw₂=w₂+fRand

dw₁=w₁+fRand

dw₃=w₃−

fRand

wherein, fRand is a parameter for fine adjusting dithering;

R(m, t) is a parameter with random value for scanning a current dot;

R_MAX is a maximum of a random parameter R(i);

cDither is a parameter for adjusting amplitude of dithering; and

dw₀˜

dw₃ are the diffusion weight coefficients of the second diffusion filter w in different directions after dithering.

10. The method of claim 2, wherein the error diffusion further comprises:

(a) scanning and inputting the original image, carrying out an operation of a threshold comparison on a final value g″

(m, t) of a current pixel in the original image, and then converting a result of the operation to an output value b(m, t) of the current pixel;

(b) comparing the output value b(m, t) of the current pixel with a medium value g′

(m, t) of the current pixel to obtain an error value e(m, t) of the current pixel;

(c) multiplying the error value e(m, t) by preset weight distribution coefficients through a first diffusion filter e and then diffusing results of the multiplying to unprocessed pixels around the current pixel, wherein each of the diffused results to the unprocessed pixels around the current pixel is weightedly added to an original value g(m, t) of the pixel M_x to obtain a new medium value g′

(m, t) of the pixel M_x;

(d) diffusing processed results to corresponding pixels M_x surrounding the current pixel, respectively, and weightedly adding each of the diffused processed results to the medium value g′

(m, t) of the corresponding pixel M_x obtained from error diffusion in the step (c) to obtain the final value g″

(m, t) of the corresponding pixel M_x, wherein the processed results are obtained by implementing a multiplying operation on the output value b(m, t) of the current pixel using a second diffusion filter w and processing results of the multiplying operation with a dithering algorithm, and the step (d) is implemented in parallel with the steps (b) and (c); and

(e) repeating the steps (a)-(d) until the original input values g(m, t) of all pixels are processed.

11. The method of claim 10, wherein the first error diffusion filter e in the step (c) uses a diffusion principle and weight distribution coefficients as below:

12. The method of claim 11, wherein a diffusion mode of the second diffusion filter w is set as:

13. The method of claim 12, wherein the dithering algorithm for the second diffusion filter w in the step (d) is as below:

fRand=(R(m,t)/R_MAX−

0.5)×

cDither

dw₀=w₀−

fRand

dw₂=w₂+fRand

dw₁=w₁+fRand

dw₃=w₃−

fRand

wherein, fRand and is a parameter for fine adjusting dithering;

R(m, t) is a parameter with random value for scanning a current dot;

R_MAX is a maximum of a random parameter R(i);

cDither is a parameter for adjusting amplitude of dithering; and

dw₀˜

dw₃ are the diffusion weight coefficients of the second diffusion filter w in different directions after dithering.

14. The method of claim 3, wherein the error diffusion further comprises:

(a) scanning and inputting the original image, carrying out an operation of a threshold comparison on a final value g″

(m, t) of a current pixel in the original image, and then converting a result of the operation to an output value b(m, t) of the current pixel;

(b) comparing the output value b(m, t) of the current pixel with a medium value g′

(m, t) of the current pixel to obtain an error value e(m, t) of the current pixel;

(c) multiplying the error value e(m, t) by preset weight distribution coefficients through a first diffusion filter e and then diffusing results of the multiplying to unprocessed pixels around the current pixel, wherein each of the diffused results to the unprocessed pixels around the current pixel is weightedly added to an original value g(m, t) of the pixel M_x to obtain a new medium value g′

(m, t) of the pixel M_x;

(d) diffusing processed results to corresponding pixels M_x surrounding the current pixel, respectively, and weightedly adding each of the diffused processed results to the medium value g′

(m, t) of the corresponding pixel M_x obtained from error diffusion in the step (c) to obtain the final value g″

(m, t) of the corresponding pixel M_x, wherein the processed results are obtained by implementing a multiplying operation on the output value b(m, t) of the current pixel using a second diffusion filter w and processing results of the multiplying operation with a dithering algorithm, and the step (d) is implemented in parallel with the steps (b) and (c); and

(e) repeating the steps (a)-(d) until the original input values g(m, t) of all pixels are processed.

15. The method of claim 14, wherein the first error diffusion filter e in the step (c) uses a diffusion principle and weight distribution coefficients as below:

16. The method of claim 15, wherein a diffusion mode of the second diffusion filter w is set as:

17. The method of claim 16, wherein the dithering algorithm for the second diffusion filter w in the step (d) is as below:

fRand=(R(m,t)/R_MAX−

0.5)×

cDither

dw₀=w₀−

fRand

dw₂=w₂+fRand

dw₁=w₁+fRand

dw₃=w₃−

fRand

wherein, fRand is a parameter for fine adjusting dithering;

R(m, t) is a parameter with random value for scanning a current dot;

R_MAX is a maximum of a random parameter R(i);

cDither is a parameter for adjusting amplitude of dithering; and

dw₀˜

dw₃ are the diffusion weight coefficients of the second diffusion filter w in different directions after dithering.

18. The method of claim 4, wherein the error diffusion further comprises:

(a) scanning and inputting the original image, carrying out an operation of a threshold comparison on a final value g″

(m, t) of a current pixel in the original image, and then converting a result of the operation to an output value b(m, t) of the current pixel;

(b) comparing the output value b(m,

     1) of the current pixel with a medium value g′

(m, t) of the current pixel to obtain an error value e(m, t) of the current pixel;

(c) multiplying the error value e(m, t) by preset weight distribution coefficients through a first diffusion filter e and then diffusing results of the multiplying to unprocessed pixels around the current pixel, wherein each of the diffused results to the unprocessed pixels around the current pixel is weightedly added to an original value g(m, t) of the pixel M_x to obtain a new medium value g′

(m, t) of the pixel M_x;

(d) diffusing processed results to corresponding pixels M_x surrounding the current pixel, respectively, and weightedly adding each of the diffused processed results to the medium value g′

(m, t) of the corresponding pixel M_x obtained from error diffusion in the step (c) to obtain the final value g″

(m, t) of the corresponding pixel M_x, wherein the processed results are obtained by implementing a multiplying operation on the output value b(m, t) of the current pixel using a second diffusion filter w and processing results of the multiplying operation with a dithering algorithm, and the step (d) is implemented in parallel with the steps (b) and (c); and

(e) repeating the steps (a)-(d) until the original input values g(m, t) of all pixels are processed.

19. The method of claim 18, wherein the first error diffusion filter e in the step (c) uses a diffusion principle and weight distribution coefficients as below:

20. The method of claim 19, wherein a diffusion mode of the second diffusion filter w is set as:

21. The method of claim 20, wherein the dithering algorithm for the second diffusion filter w in the step (d) is as below:

fRand=(R(m,t)/R_MAX−

0.5)×

cDither

dw₀=w₀−

fRand

dw₂=w₂+fRand

dw₁=w₁+fRand

dw₃=w₃−

fRand

wherein, fRand is a parameter for fine adjusting dithering;

R(m, t) is a parameter with random value for scanning a current dot;

R_MAX is a maximum of a random parameter R(i);

cDither is a parameter for adjusting amplitude of dithering; and

dw₀˜

dw₃ are the diffusion weight coefficients of the second diffusion filter w in different directions after dithering.

9. A system for scanning and processing an image using the error diffusion screening technology, comprising a scanning device, a storing device and a processing device, wherein the scanning device has an output terminal connected to an input terminal of the storing device, the storing device has an output terminal connected to an input terminal of the processing device, the scanning device scans each pixel M_i of an n^th line in an original image one by one, and a scanning result of the pixel M_i is stored to the storing device;

and

wherein the processing device processes stored data for the pixel M_i by using error diffusion, once processing for the pixel M_i is completed, a obtained value for the pixel M_i is output so that an i^th storage location in the storing device can be idle, at the same time, the scanning device scans pixels of an n+1^th line in the original image, once the i^th storage location in the storing device is idle, scanned data for a pixel in the n+1^th line is stored to the i^th storage location, and once all pixels in the n^th line have been processed, all pixels in the n+1^th line have been scanned and stored.