Method for enhancing the edge contrast of a digital image

• US 6,580,835 B1
• Filed: 06/02/1999
• Issued: 06/17/2003
• Est. Priority Date: 06/02/1999
• Status: Expired due to Term

• Current Assignee: Monument Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Eastman Kodak Company
• Inventors: Gallagher, Andrew C., Gindele, Edward B.
• Primary Examiner(s): Lee, Thomas D.
• Assistant Examiner(s): BRINICH, STEPHEN M
• Application Number:
  US09/324,239
• Time in Patent Office: 1,476 Days
• Field of Search: 382/270-275, 358/1.9, 358/475
• US Class Current: 382/274
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 7/12 Edge-based segmentation

Abstract

A method for utilizing a predetermined tone scale conversion to enhance a digital image comprised of a plurality of image pixels, each image pixel characterized by an image value, includes the steps of providing image pixels corresponding to a region of the image; identifying a statistical characteristic of the image pixels in the region; normalizing the predetermined tone scale conversion for the statistical characteristic in order to generate a normalized tone scale conversion; and performing the normalized tone scale conversion on a central pixel of the region in order to generate an enhanced output pixel. In one embodiment, a scaling function is generated based upon the statistical parameter and a first intermediate value is generated from application of the scaling function to the input pixel value. Then a second intermediate value is generated from the application of the first intermediate value to the tone scale function, and an enhanced pixel value is then obtained from application of the inverse of the scaling function to the second intermediate value.

Claims

1. A method for utilizing a predetermined tone scale conversion to enhance a digital image comprised of a plurality of image pixels, each image pixel characterized by an image value, said method comprising the steps of:

(a) providing image pixels corresponding to a region of the image;

(b) identifying a statistical characteristic of the image pixels in the region, wherein the statistical characteristic is a gradient value;

(c) normalizing the predetermined tone scale conversion for the statistical characteristic in order to generate a normalized tone scale conversion; and

(d) performing the normalized tone scale conversion on a central pixel of the region in order to generate an enhanced output pixel.

2. The method of claim 1 in which the region of step (a) comprises a two dimensional region distributed around the central pixel.

3. The method of claim 2 in which the region of step (a) comprises a 5×

5 or smaller array of image pixels.

4. The method of claim 1 in which the gradient value is derived from a maximum and a minimum value for the region.

5. The method of claim 4 in which the gradient value is computed from the difference between maximum and minimum image values of image pixels within the region.

6. The method of claim 1 in which the gradient value is computed from the difference between average maximum and minimum values across respective pluralities of image pixels comprising portions of the region.

7. The method of claim 1 in which the tone scale conversion includes the application of a predetermined tone scale function, step (c) comprises normalizing the value of the central image pixel input to the tone scale function with a scaling function based on the statistical characteristic, and step (d) comprises mapping the scaled value of the central pixel through the tone scale function to generate an intermediate output value.

8. The method of claim 7 in which step (d) further comprises processing the intermediate value of the central image pixel output from the tone scale function with a function that is the inverse of the scaling function.

9. The method of claim 1 in which the tone scale conversion includes application of a predetermined tone scale function and step (c) comprises normalizing the coordinates of the tone scale function based on the statistical characteristic.

10. The method of claim 1 in which the tone scale conversion includes application of a predetermined tone scale function, and the method further comprises the step of adjusting a parameter of the tone scale function based on the statistical characteristic of the region.

11. The method of claim 10 in which the step of adjusting a parameter of the tone scale function comprises varying the slope of the tone scale function.

12. The method of claim 1 in which the steps (a)-(d) are repeated for consecutive overlapping regions such that contiguous central pixels are processed through the tone scale conversion.

13. The method of claim 12 wherein the tone scale conversion includes application of a predetermined tone scale function to all central image pixels processed through the normalized tone scale conversion.

14. The method of claim 1 in which the tone scale conversion includes the application of a predetermined tone scale function having input and output coordinates, step (c) comprises normalizing the input coordinate of the tone scale function with a scaling function based on the statistical characteristic and normalizing the value of the central pixel output from the tone scale function based on the inverse of the scaling function, and then step (d) comprises mapping the value of the central pixel through the tone scale function to generate a scaled output pixel.

15. The method of claim 1 in which the tone scale conversion includes the application of a predetermined tone scale function having input and output coordinates, step (c) comprises normalizing the value of the central pixel input to the tone scale function with a scaling function based on the statistical characteristic and normalizing the output coordinate of the tone scale function based on the inverse of the scaling function, and then step (d) comprises mapping the scaled value of the central pixel through the tone scale function to generate a processed output pixel.

16. A method for enhancing a digital image processed through a digital image channel, the method comprising the steps of:

a) receiving a pixel value from a spatial region of the digital image;

b) receiving a tone scale function;

c) calculating a statistical parameter based on the values of other pixels in the spatial region of the digital image;

d) generating a scaling function based upon the statistical parameter;

e) generating a first intermediate value from the pixel value and the scaling function;

f) generating a second intermediate value from the first intermediate value and the tone scale function; and

g) generating an enhanced pixel value from an inverse of the scaling function, and the second intermediate value.

17. The method of claim 16 further comprising the step of repeating steps (a) and (c)-(g) in order to generate an enhanced pixel for each pixel in the digital image channel.

18. The method of claim 16 wherein the statistical parameter of step (c) is the maximum or minimum of the pixel values from the spatial region of the digital image channel.

19. The method of claim 18 wherein the statistical parameter is used to normalize the tone scale function creating a normalized tone scale function.

20. The method of claim 18 wherein the statistical parameter is used to normalize the original pixel value creating a normalized pixel value.

21. The method of claim 20 wherein the normalized pixel value is modified by the normalized tone scale function.

22. The method of claim 16 wherein the tone scale function is a predetermined sigmoid function.

23. The method of claim 17 wherein the tone scale function is a predetermined sigmoid function used for each pixel in the digital image.

24. The method of claim 19 wherein the tone scale function is a predetermined sigmoid function that is normalized to create a normalized sigmoid function.

25. The method of claim 24 wherein the normalized pixel value is modified by the normalized sigmoid function.

26. The method of claim 24 wherein the step of using a sigmoid function is further comprised of determining the standard deviation of the sigmoid function based upon the statistical parameters.