Adaptive Image De-Noising by Pixels Relation Maximization

• US 20080285881A1
• Filed: 02/07/2006
• Published: 11/20/2008
• Est. Priority Date: 02/07/2005
• Status: Abandoned Application

• Current Assignee: Ultraspect Ltd.
• Original Assignee: Ultraspect Ltd.
• Inventors: Gal, Yaniv
• Application Number:
  US11/883,513
• Publication Number:
  US 20080285881A1
• Time in Patent Office: Days
• US Class Current: 382/261
• CPC Class Codes: G01R 33/5608 Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels image data processing or generation, in general G06T
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 5/002 Denoising; Smoothing noise processing or correction adapted to be used in an image pickup device containing and electronic image sensor H04N23/81, H04N25/60 - H04N25/67
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

A method is disclosed for adaptive filtering of at least one pixel having an initial value of an image composed of pixels. The method comprises: calculating local expected value for the pixel; calculating local signal to noise ratio; calculating local filtration ratio based at least on said local signal to noise ratio; calculating a weighted average of the initial value and local expected value using said local filtration ratio as weight; and assigning the weighted average as a new value for the pixel.

Claims

1. A method for adaptive filtering of at least one pixel having an initial value of an image composed of pixels, the method comprising:

calculating local expected value for the pixel;

calculating local signal to noise ratio;

calculating local filtration ratio based at least on said local signal to noise ratio;

calculating a weighted average of the initial value and local expected value using said local filtration ratio as weight; and

assigning the weighted average as a new value for the pixel.

2. A method as claimed in claim 1, wherein the local filtration ratio is also based on the local expected value of the pixel.

3. A method as claimed in claim 1, wherein the local filtration ratio is also based on the initial value of the pixel.

4. A method as claimed in claim 1, wherein the expected value comprises a local mean value.

5. A method as claimed in claim 1, wherein the expected value comprises a local median.

6. A method as claimed in claim 1, wherein the expected value comprises a local weighted average neighborhood pixel values with respect to the pixel, after outlayer values in said neighborhood were removed.

7. A method as claimed in claim 6, wherein the expected value comprises an alpha-pruning value.

8. A method as claimed in claim 1, wherein the signal to noise ratio comprises a local standard deviation.

9. A method as claimed in claim 1, wherein the signal to noise ratio comprises a local gradient norm at the pixel.

10. A method as claimed in claim 1, wherein the signal to noise ratio comprises a Shannon'"'"'s Entropy estimator.

11. A method as claimed in claim 1, wherein the signal to noise ratio comprises a correlation between a gradient at the pixel and neighboring gradients.

12. A method as claimed in claim 1, wherein the local filtration ratio is given by the formula G=Exp [−

C/SNR] where G is the local filtration ratio, C is constant for the image and SNR is the local signal to noise ratio.

13. A method as claimed in claim 12, wherein the new value of the pixel is given by the formula F(I_v)=G_v I_v+(1−

G_v) M_v where I_v is the initial value, G_v is the filtration ratio and M_v is the expected value, all for a given pixel v.

14. A method as claimed in claim 13, wherein the new value of the pixel is calculated iteratively.

15. A method as claimed in claim 1, wherein the image is two-dimensional.

16. A method as claimed in claim 1, wherein the image is multi-dimensional.

17. A method as claimed in claim 1, wherein the initial value of the pixel is pixel raw value.

18. A method as claimed in claim 1, wherein the image is acquired in medical imaging.

19. A method as claimed in claim 18, wherein the medical imaging comprises nuclear imaging.