Image processing method for reducing jaggy effect

• US 20050219633A1
• Filed: 10/28/2004
• Published: 10/06/2005
• Est. Priority Date: 11/25/2003
• Status: Active Grant

• Current Assignee: Qisda Corporation
• Original Assignee: Qisda Corporation
• Inventors: Chien, Hui-Jan
• Granted Patent: US 7,542,174 B2
• Time in Patent Office: Days
• US Class Current: 358/3.270
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• 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
• CPC Class Codes: H04N 1/4092 Edge or detail enhancement

Abstract

An image processing method for reducing jaggy effect, which is applied in an image output device, is provided. Firstly, a continuous tone image is generated, and continuous tone pixels are defined according to a first addressing space. Then, a halftone image is generated. After that, the continuous tone image is low-pass filtered to generate a low-pass filtered image. Next, determine whether a position of the low-pass filtered image whose density is approximate to a pre-determined density. If so, generate a set of second addressing space co-ordinates of a key point corresponding to the position. Then, a moving vector corresponding to the key point is generated so as to regulate the position of a display point of the halftone pixel. Afterward, output the display point according to the position after regulation.

Claims

1. An image processing method applied in an image output device for reducing jaggy effect, comprising the steps of:

generating a continuous tone image having a plurality of continuous tone pixels, the co-ordinates of the continuous tone pixels being defined according to a first addressing space with each of the continuous tone pixels having a continuous image density and one of the continuous tone pixels being I(i, j);

halftone-processing the continuous tone image to generate a halftone image, which has a plurality of halftone pixels corresponding to the continuous tone pixels, the halftone pixels being at an ON state or an OFF state, while the halftone pixel HT(i, j) corresponding to continuous tone pixel I(i, j);

low-pass filtering the continuous tone image to generate a low-pass filtered image having a plurality of low-pass filtered pixels corresponding to the continuous tone pixels, a low-pass filtered pixel B(i, j) corresponding to the continuous tone pixel (i, j), and each of the low-pass filtered pixels having a low-pass filtered image density;

determining whether a position of the low-pass filtered image whose density is approximate to a pre-determined density can be obtained in the low-pass filtered pixel B(i, j);

if so, define the position according to a second addressing space to obtain a set of second addressing space co-ordinates (Vr, Vc) of a key point KP(i, j) corresponding to the position;

determining whether the key point KP(i, j) corresponds to a convex image region or a concave image region according to the relationship between the key point KP(i, j) and at least two of its adjacent key points, obtain a moving vector corresponding to the key point, and regulate the position of a display point of the halftone pixel HT(i, j) according to the moving vector; and

outputting the display point according to the position after regulation.

2. The image processing method according to claim 1, wherein an approximately linear contour path is formed by the key point KP(i, j) and at least two of its adjacent key points.

3. The image processing method according to claim 1, wherein the first addressing space is a low-resolution addressing space, while the second addressing space is a high-resolution addressing space.

4. The image processing method according to claim 1, wherein the image processing method is applied in a printer.

5. The image processing method according to claim 1, wherein the image processing method is applied in an ink-jet printer.

6. The image processing method according to claim 1, wherein the display point comprises cyaneus (C), magenta (M), yellow (Y) and black (K) dots.

7. The image processing method according to claim 1, wherein the key point KP(i, j) and two of its adjacent key points correspond to a first contour vector and a second contour vector, when the key point KP(i, j) corresponds to a convex image region, the distance between the first contour vector and a corresponding reference point of the moving vector equals (1/t) times the radius of the display point, while the distance from the reference point Q to the first contour vector V2 also equals (1/t) times the radius of the display point, t is a positive real number.

8. The image processing method according to claim 7, where t equals {square root}{square root over (2)}.

9. The image processing method according to claim 1, wherein the key point KP(i, j) and two of its adjacent key points correspond to a first contour vector and a second contour vector, a pre-determined area of a sector region is formed by the first contour vector, the second contour vector, and a circular region whose center is a corresponding reference point of the moving vector and radius is the radius of the display point.

10. The image processing method according to claim 9, wherein the pre-determined area is (π

/2−

1)/4 times the area of a halftone pixel.

11. The image processing method according to claim 1, wherein the step of determining whether a position of the low-pass filtered image whose density is approximate to a pre-determined density can be obtained in the low-pass filtered pixel B(i, j) further comprises:

(a1) calculating plural row averages of the low-pass filtered image densities of plural rows of the low-pass filtered pixels disposed at a corresponding local region of the low-pass filtered pixel B(i, j) as well as plural column averages of the low-pass filtered image densities of plural columns of the low-pass filtered pixels disposed at a corresponding local region of the low-pass filtered pixel B(i, j);

(a2) using the interpolation method to obtain a second addressing space row co-ordinate Vr0 whose low-pass filtered image density is approximate to the pre-determined value according to the row averages, and if the second addressing space row co-ordinate Vr0 is within the corresponding row region of the low-pass filtered pixel B(i, j), then proceed to step (a3), otherwise, proceed to (a4);

(a3) determining whether the corresponding low-pass filtered image density column average of the low-pass filtered pixel B(i, j) is the median of the column averages;

if yes, set MarkR(i, j), a row mark value of the low-pass filtered pixel B(i, j), to be a first value;

otherwise, set MarkR(i, j) to be a second value;

(a4) using the interpolation method to obtain a second addressing space column co-ordinate Vc0 whose low-pass filtered image density is approximate to the pre-determined value according to the column averages, and if the second addressing space column co-ordinate Vc0 is within the corresponding column region of the low-pass filtered pixel B(i, j), then proceed to step (a5), otherwise, proceed to (a6);

(a5) determining whether the corresponding low-pass filtered image density row average of the low-pass filtered pixel B(i, j) is the median of the row averages;

if yes, set MarkC(i, j), a column mark value of the low-pass filtered pixel B(i, j), to be the first value;

otherwise, set MarkC(i, j) to be the second value

(a6) recording the second addressing space row co-ordinate Vr0 and the second addressing space column co-ordinate Vc0, and setting the second addressing space co-ordinates (Vr0, Vc0) to be the key point KP(i, j).

12. The image processing method according to claim 11, wherein the step of determining whether the key point KP(i, j) corresponds to a convex image region or a concave image region further comprises:

(b1) proceeding to step (b2) if both the column mark value MarkC(i, j) and the row mark value MarkR(i, j) of the low-pass filtered pixel are the first value;

(b2) identifying KP1 and KP2, the two key points most close to the key point KP(i, j);

(b3) calculating a row density change and a column density change of the corresponding local region of the low-pass filtered pixel, and obtaining a gradient vector GR according to the row density change and the column density change;

(b4) obtaining a first contour vector V1 and a second contour vector V2 whose initial point is the key point KP(i, j) and respective destinations are the key point KP1 and the key point KP2, and obtaining a moving vector whose direction is approximately parallel to the angular bisector of the angle contained by the first contour vector V1 and the second contour vector V2, the moving vector further containing an acute angle with the gradient vector GR;

(b5) determining whether the key point KP(i, j) corresponds to a convex image region or a concave image region according to the moving vector, the first contour vector and the second contour vector;

proceed to step (b6) if the key point KP(i, j) corresponds to a convex image region and proceed to step (b7) if the key point KP(i, j) corresponds to a concave image region;

(b6) obtaining a reference point, the distance between the reference point and the first contour vector being equal to (1/t) times the radius of the display point, and the distance between the reference point and the second contour vector also being equal to (1/t) times the radius of the display point, t being a positive real number;

(b7) obtaining a reference point which is used as the central point of a circular region whose radius equals the radius of a display point, the area of a sector region formed by the circular region, the first contour vector, and the second contour vector being a pre-determined area;

(b8) obtaining the moving vector whose initial point is set to be the original point of the second addressing space co-ordinate and destination is set to be the reference point.

13. The image processing method according to claim 12, wherein t equals {square root}{square root over (2)}A, while the pre-determined is (π

/2−

1)/4 times the area of a halftone pixel.-determined area is (π

2−

1)/4 times the area of a halftone pixel.

14. The image processing method according to claim 12, wherein the key point KP(i, j) corresponds to the concave image region if the inner product of the moving vector and the first contour vector is negative and so is the inner product of the moving vector and the second contour vector.

15. The image processing method according to claim 12, wherein the key point KP(i, j) corresponds to the convex image region if the inner product of the moving vector and the first contour vector is positive and so is the inner product of the moving vector and the second contour vector.

16. The image processing method according to claim 12, wherein the inter-phase between step (b7) and step (b8) further comprises:

(c1) determining whether the halftone pixel HT(i, j) is at an ON state;

if yes, proceed to step (c2), otherwise, proceed to step (c3);

(c2) moving the center of the display point to be close to the reference, then proceeding to step (b8); and

(c3) adding a second display point to the halftone pixel HT(i, j) if the density of any of the continuous tone pixel disposed at the corresponding local region of the halftone pixel HT(I, j) is larger than a high critical density, the center of the second display point being close to the reference point.

17. The image processing method according to claim 16, wherein the step of regulating the position of the display point of the halftone pixel HT(i, j) according to the moving vector comprises:

outputting the display point according to the position after regulation or outputting the second display point according to the position of the second display point.

18. The image processing method according to claim 1, wherein the image processing method further comprises:

determining whether the corresponding local region of the key point KP(ii, j) match one of a plurality of particular patterns;

if yes, obtain the moving vector according to the matched particular pattern.

19. The image processing method according to claim 1, wherein the low-pass filter processing is a processing of anti-aliasing algorithm.

20. The image processing method according to claim 1, wherein the low-pass filter processing is a Gaussian-blurred processing.