METHOD AND SYSTEM FOR NOISE LEVEL DETECTION IN IMAGE DATA

• US 20090257674A1
• Filed: 04/11/2008
• Published: 10/15/2009
• Est. Priority Date: 04/11/2008
• Status: Active Grant

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Schweid, Stuart A.
• Granted Patent: US 8,208,753 B2
• Time in Patent Office: Days
• US Class Current: 382/263
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06V 10/30 Noise filtering

Abstract

A system determines the noise level of image data by high pass filtering image data. Absolutes values of the high pass filtered image data are determined. Thereafter, multiple mean values for absolute values less than a predetermined number of threshold values are determined. Based upon the determined mean values, a plurality of estimated mean values is calculated, each estimated mean value being calculated from a combination of two determined mean values. The noise of the image is determined from a combination of the minimum estimated mean value and the maximum estimated mean value. This noise can be optionally used by a sigma filter, at Step S740, to sigma filter the image data.

Claims

1. A method for determining a noise level of image data, comprising:

(a) high pass filtering the image data;

(b) determining absolutes values of the high pass filtered image data;

(c) determining a mean value of the absolute values; and

(d) determining, based upon the determined mean value, the noise of the image.

2. The method as claimed in claim 1, wherein said determining a mean value of the absolute values comprises:

(c1) determining, using a predetermined number of threshold values, multiple mean values of the absolute values, each mean value being calculated using absolutes values less than a predetermined threshold value; and

(c2) determining, based upon the determined mean values, an estimated mean value, the estimated mean value being a combination of two of the multiple mean values;

said determining the noise of the image being based upon the determined estimated mean value.

3. The method as claimed in claim 2, wherein the estimated mean value is calculated by multiplying a first mean value by two and subtracting a second mean value.

4. The method as claimed in claim 3, wherein the first mean value is a mean value calculated from absolute values less than K*N and the second mean value is a mean value calculated from absolute values less than (K−

1)*N wherein K is an integer and N is a predetermined maximum absolute value.

5. The method as claimed in claim 1, wherein said determining a mean value of the absolute values comprises:

(c1) determining, using a predetermined number of threshold values, multiple mean values of the absolute values, each mean value being calculated using absolutes values less than a predetermined threshold value;

(c2) determining, based upon the determined mean values, an estimated mean value, the estimated mean value being a combination of two of the multiple mean values; and

(c3) determining a final estimated mean value;

said determining the noise of the image being based upon the determined estimated mean value.

6. The method as claimed in claim 5, wherein the estimated mean value is calculated by multiplying a first mean value by two and subtracting a second mean value.

7. The method as claimed in claim 6, wherein the first mean value is a mean value calculated from absolute values less than K*N and the second mean value is a mean value calculated from absolute values less than (K−

1)*N wherein K is an integer and N is a predetermined maximum absolute value.

8. The method as claimed in claim 5, wherein the final estimated mean value is calculated by multiplying a maximum estimated mean value by two and subtracting a minimum estimated mean value.

9. The method as claimed in claim 6, wherein the final estimated mean value is calculated by multiplying a maximum estimated mean value by two and subtracting a minimum estimated mean value.

10. The method as claimed in claim 7, wherein the final estimated mean value is calculated by multiplying a maximum estimated mean value by two and subtracting a minimum estimated mean value.

11. A system for determining a noise level of image data, comprising:

a first filter to high pass filter the image data;

a mean circuit, operatively connected to said first filter, to determine absolutes values of the high pass filtered image data and to determine a mean value of the absolute values; and

a noise level circuit, operatively connected to said mean circuit, to determine, based upon the determined mean value, the noise of the image.

12. The system method as claimed in claim 11, wherein said mean circuit determines, using a predetermined number of threshold values, multiple mean values of the absolute values, each mean value being calculated using absolutes values less than a predetermined threshold value, and determines, based upon the determined mean values, an estimated mean value, the estimated mean value being a combination of two of the multiple mean values;

said noise level circuit determining the noise of the image being based upon the determined estimated mean value.

13. The system as claimed in claim 12, wherein the estimated mean value is calculated by multiplying a first mean value by two and subtracting a second mean value.

14. The system as claimed in claim 13, wherein the first mean value is a mean value calculated from absolute values less than K*N and the second mean value is a mean value calculated from absolute values less than (K−

1)*N wherein K is an integer and N is a predetermined maximum absolute value.

15. The system as claimed in claim 11, wherein said mean circuit determines, using a predetermined number of threshold values, multiple mean values of the absolute values, each mean value being calculated using absolutes values less than a predetermined threshold value;

determines, based upon the determined mean values, an estimated mean value, the estimated mean value being a combination of two of the multiple mean values; and

determines a final estimated mean value;

said noise level circuit determining the noise of the image being based upon the determined estimated mean value.

16. The system as claimed in claim 15, wherein the estimated mean value is calculated by multiplying a first mean value by two and subtracting a second mean value.

17. The system as claimed in claim 16, wherein the first mean value is a mean value calculated from absolute values less than K*N and the second mean value is a mean value calculated from absolute values less than (K−

1)*N wherein K is an integer and N is a predetermined maximum absolute value.

18. The system as claimed in claim 15, wherein the final estimated mean value is calculated by multiplying a maximum estimated mean value by two and subtracting a minimum estimated mean value.

19. The system as claimed in claim 16, wherein the final estimated mean value is calculated by multiplying a maximum estimated mean value by two and subtracting a minimum estimated mean value.

20. The system as claimed in claim 17, wherein the final estimated mean value is calculated by multiplying a maximum estimated mean value by two and subtracting a minimum estimated mean value.