Noise reduction in an image

• US 5,825,846 A
• Filed: 12/20/1996
• Issued: 10/20/1998
• Est. Priority Date: 12/21/1995
• Status: Expired due to Fees

• Current Assignee: US Philips Corporation (Koninklijke Philips N.V.)
• Original Assignee: US Philips Corporation (Koninklijke Philips N.V.)
• Inventors: Aach, Til, Kunz, Dietmar W.
• Primary Examiner(s): Porta, David P.
• Assistant Examiner(s): Bruce, David Vernon
• Application Number:
  US08/770,363
• Time in Patent Office: 669 Days
• Field of Search: 378/62, 378/98, 378/901, 250/370.09
• US Class Current: 378/98
• CPC Class Codes: G06T 5/20 using local operators

Abstract

In a method of processing an image the image is divided in one or more blocks. Separate blocks are spatially frequency transformed in that pixel-values of the blocks are transformed into spectral coefficients. A noise level of the image is estimated and reduced spectral coefficients are derived from spectral coefficients and the estimated noise level. Pixel-values for a processed block are synthesized from the reduced spectral coefficients and the processed blocks are assembled into a processed image. The noise level is estimated from the image information within the image. Preferably, a few parameters relating to the circumstances under which the image was acquired are also taken into account for estimating the noise level.

Claims

1. Method of processing an image comprising deriving spectral coefficients from the image, estimating a noise level of the image, deriving reduced spectral coefficients from said spectral coefficients and the estimated noise level, and synthesizing a processed image from said reduced spectral coefficients, characterized in that the noise level of the image is estimated mainly from the image, and not from any other image.

2. A method of processing an image as claimed in claim 1, characterized in that before deriving the spectral coefficients for a separate block, absolute values of pixel-values of a boundary region of said block are decreased.

3. A method of processing an image as claimed in claim 1, characterized in that for deriving the reduced spectral coefficients, a spatial distribution in the image of image information to which the spectral coefficients relate is taken into account.

4. A method of processing an image as claimed in claim 1, characterized in that estimating the noise level involves computation of the statistical variances of the spectral coefficients, and the reduced spectral coefficients are derived from said statistical variances and the spectral coefficients.

5. A method of processing an image as claimed in claim 4, characterized in that before deriving the spectral coefficients for a separate block, absolute values of pixel-values of a boundary region of said block are decreased.

6. A method of processing an image as claimed in claim 1, characterized in that separate reduced spectral coefficients are computed by multiplying spectral coefficients by an attenuation function, having a range in the interval 0,1 of the ratio of said spectral coefficient and its statistical variance.

7. A method of processing an image as claimed in claim 6, characterized in that the attenuation function is an increasing function.

8. Method of processing an image comprising dividing the image into several blocks, and for separate blocks, deriving spectral coefficients, estimating a noise level, deriving reduced spectral coefficients from spectral coefficients and said noise level of the relevant block, synthesizing processed blocks from said reduced spectral coefficients, and assembling processed blocks into a processed image, characterized in that said noise levels are estimated mainly from respective blocks of the image, and not from any other image.

9. A method of processing an image as claimed in claim 8, characterized in that separate reduced spectral coefficients are computed by multiplying spectral coefficients by an attenuation function, having a range in the interval 0,1 of the ratio of said spectral coefficient and its statistical variance.

10. A method of processing an image as claimed in claim 8, characterized in that before deriving the spectral coefficients for a separate block, absolute values of pixel-values of a boundary region of said block are decreased.

11. A method of processing an image as claimed in claim 8, characterized in that estimating the noise level involves computation of the statistical variances of the spectral coefficients, and the reduced spectral coefficients are derived from said statistical variances and the spectral coefficients.

12. A method of processing an image as claimed in claim 11, characterized in that separate reduced spectral coefficients are computed by multiplying spectral coefficients by an attenuation function, having a range in the interval 0,1 of the ratio of said spectral coefficient and its statistical variance.

13. A method of processing an image as claimed in claim 8, characterized in that respective noise levels are derived from average brightness values of separate blocks.

14. A method of processing an image as claimed in claim 13, characterized in that before deriving the spectral coefficients for a separate block, absolute values of pixel-values of a boundary region of said block are decreased.

15. A method of processing an image as claimed in claim 13, characterized in that separate reduced spectral coefficients are computed by multiplying spectral coefficients by an attenuation function, having a range in the interval 0,1 of the ratio of said spectral coefficient and its statistical variance.

16. A method of processing an image as claimed in claim 13, characterized in that estimating the noise level involves computation of the statistical variances of the spectral coefficients, and the reduced spectral coefficients are derived from said statistical variances and the spectral coefficients.

17. A method of processing an image as claimed in claim 16, characterized in that separate reduced spectral coefficients are computed by multiplying spectral coefficients by an attenuation function, having a range in the interval 0,1 of the ratio of said spectral coefficient and its statistical variance.

18. An image processing system comprising:

a block generator for dividing the image into several blocks;

a transformer unit for deriving sets of spectral coefficients from said blocks;

a noise estimator for estimating respective noise levels of said blocks;

a noise attenuator for deriving sets of reduced spectral coefficients for said blocks from said spectral coefficients and said noise levels;

a synthesizing unit for synthesizing processed blocks from respective sets of reduced spectral coefficients; and

an assembler unit for assembling processed blocks into a processed image;

characterized in that the noise estimator is arranged to estimate said noise levels mainly from respective blocks, in particular from one or more local average brightness values of respective blocks.

19. An x-ray examination apparatus comprising an x-ray detector for deriving an image signal from an x-ray image, and an image processing system for processing the image signal, the image processing system comprising:

a block generator for dividing the image signal into block signals representing respective blocks;

a transformer unit for deriving sets of spectral coefficients from respective block signals;

a noise estimator for estimating respective noise levels of said block signals;

a noise attenuator for deriving sets of reduced spectral coefficients for said blocks from spectral coefficients and said noise levels;

a synthesizing unit for synthesizing processed block signals from sets of reduced spectral coefficients, and

an assembler unit for assembling processed block signals into a processed image signal;

characterized in that the noise estimator is arranged to estimate said noise levels mainly from respective block signals, in particular from one or more local average signal levels of respective block signals.

20. An x-ray examination apparatus as claimed in claim 19, characterized in that the noise estimator is arranged to take imaging parameters into account for estimating the noise.