Method for Controlling the Shapes of FM-AM Mixed Dots on a Multi-Bit Depth Imaging Apparatus

• US 20080285085A1
• Filed: 04/29/2006
• Published: 11/20/2008
• Est. Priority Date: 10/26/2005
• 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), Beijing Founder Electronics Company Limited (Peking University), Peking University
• Inventors: Yang, Bin, Li, Haifeng
• Granted Patent: US 8,045,233 B2
• Time in Patent Office: Days
• US Class Current: 358/3.06
• CPC Class Codes: H04N 1/4053 with threshold modulated relative to input image data or vice versa
• CPC Class Codes: H04N 1/4057 the pattern being a mixture of differently sized sub-patterns, e.g. spots having only a few different diameters multi-toning H04N1/40087

Abstract

Disclosed is a method for controlling the shapes of FM-AM mixed halftone dots on the multi-bit depth imaging apparatus. In the prior art, since the reproduction of the shapes of the dots in various gradations is absolutely based on the theory of random error diffusion and is influenced by the dynamic controlling output mechanism for the multi-bit dots, it is hard to assure the controllability of the shapes of the dots in a certain gradation. Based on the prior art, the dynamic statistic algorithm with adjacent output gray levels is introduced to assure the controllability of the shapes of the dots and solve the problem of random change of the shapes of the dots due to the randomicity of the error diffusion. According to the disclosed method, the features of the multi-bit imaging apparatus can be achieved fully in light of the requirements of the dots on the basis of the original method for multi-bit FM-AM mixed screening using error diffusion based on dual-feedback. The effect of FM-AM mixed halftone screening can be achieved under low resolution with controllable shapes of the dots, The problem of granular sensation can be solved during the practical output of the mixed halftone dots so as to assure the smooth effect of the gradations.

Claims

1-10. -10. (canceled)

11. A method for controlling shapes of FM-AM mixed dots on a multi-bit depth imaging apparatus, comprising:

1) dividing averagely an interval [0, 255] into 2ⁿ-1 gradations in light of a bit depth n of the apparatus;

[0, R₁], (R₁,R₂], . . . , (R<sub>i−

1</sub>, R_i], . . . (R_2-2ⁿ, 255], wherein i is a positive integer and less than 2ⁿ-2, corresponding ranges of a dot-matrix of bit-outputting are

(0, Out₁), (Out₁, Out₂), . . . , (Out<sub>i−

1</sub>, Out_i), . . . (Out_2-2ⁿ, 11 . . .

     1), the Out_i being a binary representation of the n-bit depth, and

a threshold M_i of a central point of each of the gradations is sampled as a threshold comparison parameter for the gradation;

2) setting output probability thresholds with a n-bit imaging depth in the interval [0, 255];

3) processing respectively the dots in the 2ⁿ-1 gradations (R_i-1, R_i) based on an FM-AM mixed screening process using a dual-feedback error diffusion; and

4) computing dynamically output dot-matrix data, by using a known dynamic gradation-changeable output mechanism and a dynamic statistic algorithm with adjacent output gray levels in light of the probability thresholds F_i and an accumulated value ShapeCur for controlling the shape of a current dot, to control the shapes of the dots, when mixed screening in the gradations (R_1-1, R_i) is achieved.

12. The method of claim 11, wherein the step 2) further comprises

setting 2ⁿ-2 integers L₁, L₂, . . . , L_i, . . . , L_2-2ⁿ as the output probability thresholds with the n-bit imaging depth, and

adjusting the probability thresholds based on requirements of the apparatus.

13. The method of claim 11, wherein the step 4) further comprises:

(a) determining density zones to be adjusted for controlling the shapes of the dots in light of a linear output feature of the apparatus;

(b) determining the shapes of the dots to be adjusted in light of parameters for adjusting a pulse-width in the apparatus, existing random shapes of the dots in the density zones, and requirements relating to a stability of the apparatus;

(c) determining desired and undesired shapes of the dots, respectively, in light of the determined shapes of the dots to be adjusted in the step (b) and imaging features of the apparatus; and

(d) setting controlled dots around the current dot by using the dynamic statistic algorithm with the adjacent output gray levels, in light of the density zones of the FM-AM mixed dots and existing output gray level gradations, so as to work out output range parameters of the mixed dots.

14. The method of claim 13, wherein the dynamic statistic algorithm in the step (d) comprises:

i) letting the output gray level of a dot which is preceding to the current dot be a and that of a dot which is preceding to the dot with the output grey level a be b;

ii) letting the output gray level of a dot which is above the current dot be c, that of a dot which is preceding to the dot with the output grey level c be d, and that of a dot which is following to the dot with the output grey level c be e;

iii) letting the output gray level of a dot which is above the dot with the output grey level c be f; and

iv) letting statistic parameters for the output gray levels around the current dot as below;

15. The method of claim 11, wherein the dynamic gradation-changeable output mechanism in the step 4) comprises;

generating a pseudo-random value of the current dot in light of ShapeCur;

F_i=random(ShapeCur) 

 

Formula 1

wherein, the pseudo-random function random is to be generated automatically in a compiling environment, F_iε

[0, 255]; and

the output dot-matrix data are computed dynamically;

16. The method of claim 12, wherein the dynamic gradations changeable output mechanism in the step 4) comprises:

generating a pseudo-random value of the current dot in light of ShapeCur;

F_i=random(ShapeCur) 

 

Formula 1

wherein, the pseudo-random function random is to be generated automatically in a compiling environment, F_iε

[0, 255]; and

the output dot-matrix data are computed dynamically;

17. The method of claim 13>

wherein the dynamic gradation-changeable output mechanism in the step

     4) comprises;

generating a pseudo-random value of the current dot in light of ShapeCur;

F_i=random(ShapeCur) 

 

Formula 1

wherein, the pseudo-random function random is to be generated automatically in a compiling environment, F_iε

[0, 255]; and

the output dot-matrix data are computed dynamically;

18. The method of claim 14, wherein the dynamic gradation-changeable output mechanism in the step 4) comprises:

generating a pseudo-random value of the current dot in light of ShapeCur;

F_i=random(ShapeCur) 

 

Formula 1

wherein, the pseudo-random function random is to be generated automatically in a compiling environment, F_iε

[0, 255]; and

the output dot-matrix data are computed dynamically;

19. The method of claim 15, wherein the following two processes for controlling dynamically the output gray levels are used in the step 4):

a process for dynamic gradation-changeable output and a dynamic statistic process with the adjacent output gray levels,

20. The method of claim 16, wherein the following two processes for controlling dynamically the output gray levels are used in the step 4):

a process for dynamic gradation-changeable output and a dynamic statistic process with the adjacent output gray levels.

21. The method of claim 17, wherein the following two processes for controlling dynamically the output gray levels are used in the step 4):

a process for dynamic gradation-changeable output and a dynamic statistic process with the adjacent output gray levels.

22. The method of claim 18, wherein the following two processes for controlling dynamically the output gray levels are used in the step 4):

a process for dynamic gradation-changeable output and a dynamic statistic process with the adjacent output gray levels.

23. The method of claim 11, wherein the step 3) further comprises:

(a) carrying out an operation T of a threshold comparison on a final input value g″

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

(b) comparing the value b(m, t) of the current pixel with all input value g′

(m, t) of the current pixel to obtain a difference between b(m, t) and g′

(m, t), wherein the difference is an error value e(m, t), and the input value g′

(m, t) is used for obtaining the threshold;

(c) multiplying the error value e(m, t) by preset weight distribution coefficients through an error 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 input value g(m, t) of the corresponding pixel of the original image to obtain an input value g′

(m, t) of the corresponding pixel of the original image;

(d) diffusing processed results to corresponding unprocessed pixels surrounding the current pixel, respectively, and weightedly adding each of the diffused processed results to the original input value g(m, t) of the corresponding pixel of the original image to obtain the final input value g″

(m, t) of the corresponding pixel, wherein the processed results are obtained by implementing a multiplying operation on the output value b(m, t) of the current pixel using a 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.

24. The method of claim 23, wherein the step (a) uses a process of bidirectional scanning when the original image is scanned, wherein, when a certain row is scanned from left to right, a next row is subsequently scanned from right to left.

25. The method of claim 23, wherein the error diffusion filter e uses a diffusion principle and a weight distribution mode as below:

26. The method of claim 24, wherein the error diffusion filter e uses a diffusion principle and a weight distribution mode as below:

27. The method of claim 25, wherein a diffusion mode of the diffusion filter w is set as;

28. The method of claim 26, wherein a diffusion mode of the diffusion filter w is set as: