Determining parameters for adjusting images

• US 7,783,127 B1
• Filed: 11/18/2008
• Issued: 08/24/2010
• Est. Priority Date: 10/03/2003
• Status: Expired due to Term

• Current Assignee: Adobe Inc.
• Original Assignee: Adobe Systems Incorporated (Adobe Inc.)
• Inventors: Wilensky, Gregg D.
• Primary Examiner(s): Mehta; Bhavesh M
• Assistant Examiner(s): Motsinger; Sean
• Application Number:
  US12/273,522
• Time in Patent Office: 644 Days
• Field of Search: 382168-172, 382254-275
• US Class Current: 382/274
• CPC Class Codes: G06T 2207/20012 Locally adaptive
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 5/001 Image restoration
• CPC Class Codes: G06V 10/30 Noise filtering

Abstract

Methods and apparatus, including computer program products, for determining parameter values for adjusting an image. A first function of a local attribute is specified based on values of the local attribute in the image. A second function of the local attribute is specified based on an image adjustment depending upon an adjustment parameter. An object function value is calculated for each of two or more values of the adjustment parameter, each object function value including accumulated differences between the first and second function at multiple values of the local attribute. Based on the calculated object function values, a value of the adjustment parameter is determined for adjusting the image.

Claims

1. A method for determining a value of an adjustment parameter for adjusting an image, the method comprising:

specifying a first function of a local attribute based on values of the local attribute in the image;

specifying a second function of the local attribute and the adjustment parameter;

calculating an object function value, with one or more programmable processors for each of two or more test values of the adjustment parameter, where calculating an object function value for each test value comprises;

evaluating the first function and the second function at a plurality of values of the local attribute, where evaluating the second function includes using the test value;

accumulating differences between the first and second function at the plurality of values of the local attribute according to a functional weight that depends on the value of the local attribute;

based on the calculated object function values and at least one of the two or more test values, determining the value of the adjustment parameter for adjusting the image and storing the value in a memory.

2. The method of claim 1, wherein:

specifying the first function of the local attribute includes specifying the first function based on modified values of the local attribute generated by another image adjustment when applied to the image.

3. The method of claim 1, wherein:

specifying the first function of the local attribute includes specifying the first function based on a cumulative distribution of the values of the local attribute in the image.

4. The method of claim 3, further comprising:

specifying the cumulative distribution based on a density histogram generated by binning values of the local attribute in the image into predetermined intervals.

5. The method of claim 3, wherein:

the cumulative distribution is a contrast-constrained cumulative distribution.

6. The method of claim 1, wherein:

specifying the second function of the local attribute includes specifying an attribute mapping for the local attribute based on an image adjustment, the attribute mapping depending on the adjustment parameter.

7. The method of claim 6, wherein the attribute mapping is specified by a non-local function depending, for each location within the image, on a neighborhood intensity characterizing pixel values in a neighborhood surrounding the location.

8. The method of claim 7, wherein:

specifying the second function of the local attribute includes, for each location within the image, substituting the corresponding neighborhood intensity with a pixel value at the location.

9. The method of claim 6, wherein:

specifying the second function of the local attribute includes specifying a composite function of the local attribute based on the attribute mapping and a non-linear function defining a desired distribution for the local attribute.

10. The method of claim 9, wherein the desired distribution corresponds to a gaussian density of the local attribute.

11. The method of claim 1, wherein calculating the object function values includes:

accumulating differences between a center value of the local attribute and values of the second function at the plurality of values of the local attribute; and

combining the accumulated differences between the first and second functions with the accumulated differences between the center value and the second function.

12. The method of claim 1, wherein:

calculating the object function values includes accumulating squared differences between the first and second function at the plurality of values of the local attribute.

13. The method of claim 1, wherein:

determining the value of the adjustment parameter for adjusting the image includes finding an adjustment parameter value for which the object function value is minimal.

14. The method of claim 1, further comprising:

adjusting the image using the value of the adjustment parameter.

15. The method of claim 1, wherein the local attribute depends on luminosity.

16. The method of claim 1, wherein the local attribute depends on a color value.

17. The method of claim 14, wherein adjusting the image includes separate tone adjustments for different tones.

18. The method of claim 17, wherein the tone adjustments include a shadow adjustment and a highlight adjustment.

19. The method of claim 1, wherein the step of calculating an object function value is performed by an image processor of a system for image processing.