Method of normalising a digital signal representation of an image

• US 20030161517A1
• Filed: 01/30/2003
• Published: 08/28/2003
• Est. Priority Date: 02/22/2002
• Status: Active Grant

• Current Assignee: Agfa Nv (Agfa-Gevaert N.V.)
• Original Assignee: AGFA Healthcare NV (Agfa-Gevaert N.V.)
• Inventors: Vuylsteke, Pieter
• Granted Patent: US 7,321,674 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/20064 Wavelet transform [DWT]
• CPC Class Codes: G06T 5/009 Global, i.e. based on properties of the image as a whole applied in cameras using an electronic image sensor H04N23/80, H04N23/70
• CPC Class Codes: G06T 5/30 Erosion or dilatation, e.g. thinning
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/92 based on global image properties

Abstract

A digital signal representation of an image is normalised by applying a normalisation parameter to all pixels of the digital signal representation of the image or to the pixels of a multi-scale representation of the image. The normalisation parameter can be derived from the digital signal representation itself or from a multi-scale representation of the image. Different criteria for deriving the normalisation parameter are disclosed.

Claims

1. A method of normalising a digital signal representation of an image characterised in that

said digital signal representation is decomposed into a multi-scale representation comprising at least two detail images representing detail at successive scales,

a normalisation parameter is derived from said multi-scale image representation, and

said normalisation parameter is applied to all pixels of said multi-scale representation.

4. A method according to claim 1 wherein said normalisation parameter is obtained by the steps of

deriving a representative grey value r1 from a histogram of grey values of pixels of said image,

mapping said representative grey value onto a constant reference level Tr,

determining said normalisation parameter as Tr/r1.

7. A method according to claim 4 wherein said representative grey value is determined by the steps of

calculating a restricted grey value histogram of pixels of said image having local contrast-to-noise ratio between predetermined margins,

determining a representative grey value as median of said restricted grey value histogram.

10. A method according to claim 4 wherein said normalisation parameter is the ratio of a predefined target noise level value and a value representing an estimation of the noise level.

13. A method according to claim 4 wherein said normalisation parameter is the ratio of a predefined target contrast level value and a value representing the original contrast level.

16. A method according to claim 13 wherein said original contrast level is determined by computing the histogram of local standard deviation at a predefined scale of said multi-scale representation and by calculating the median value of the local standard deviations in the histogram.

19. A method according to claim 1 wherein said normalisation parameter is a combination of the parameters

22. A method according to claim 1 wherein said normalisation parameter is the product of

25. A computer program product adapted to carry out the steps of claim 1 when run on a computer.

28. A computer readable carrier medium comprising computer executable program code adapted to carry out the steps of claim 1.

2. A method of normalising a digital signal representation of an image characterised in that

said digital signal representation is decomposed into a multi-scale representation comprising at least two detail images representing detail at successive scales,

a normalisation parameter is derived from said multi-scale image representation, and

said normalisation parameter is applied to said digital signal representation.

5. A method according to claim 2 wherein said normalisation parameter is obtained by the steps of

deriving a representative grey value r1 from a histogram of grey values of pixels of said image,

mapping said representative grey value onto a constant reference level Tr,

determining said normalisation parameter as Tr/r1.

8. A method according to claim 5 wherein said representative grey value is determined by the steps of

calculating a restricted grey value histogram of pixels of said image having local contrast-to-noise ratio between predetermined margins,

determining a representative grey value as median of said restricted grey value histogram.

11. A method according to claim 5 wherein said normalisation parameter is the ratio of a predefined target noise level value and a value representing an estimation of the noise level.

14. A method according to claim 5 wherein said normalisation parameter is the ratio of a predefined target contrast level value and a value representing the original contrast level.

17. A method according to claim 14 wherein said original contrast level is determined by computing the histogram of local standard deviation at a predefined scale of said multi-scale representation and by calculating the median value of the local standard deviations in the histogram.

20. A method according to claim 2 wherein said normalisation parameter is a combination of the parameters

23. A method according to claim 2 wherein said normalisation parameter is the product of

26. A computer program product adapted to carry out the steps of claim 2 when run on a computer.

29. A computer readable carrier medium comprising computer executable program code adapted to carry out the steps of claim 2.

3. A method of normalising a digital signal representation of an image characterised in that

a normalisation parameter is derived from said digital signal representation,

said digital signal representation is decomposed into a multi-scale representation comprising at least two detail images representing detail at successive scales, and

said normalisation parameter is applied to the pixels of said multi-scale representation.

6. A method according to claim 3 wherein said normalisation parameter is obtained by the steps of

deriving a representative grey value r1 from a histogram of grey values of pixels of said image,

mapping said representative grey value onto a constant reference level Tr,

determining said normalisation parameter as Tr/r1.

9. A method according to claim 6 wherein said representative grey value is determined by the steps of

calculating a restricted grey value histogram of pixels of said image having local contrast-to-noise ratio between predetermined margins,

determining a representative grey value as median of said restricted grey value histogram.

12. A method according to claim 6 wherein said normalisation parameter is the ratio of a predefined target noise level value and a value representing an estimation of the noise level.

15. A method according to claim 6 wherein said normalisation parameter is the ratio of a predefined target contrast level value and a value representing the original contrast level.

18. A method according to claim 15 wherein said original contrast level is determined by computing the histogram of local standard deviation at a predefined scale of said multi-scale representation and by calculating the median value of the local standard deviations in the histogram.

21. A method according to claim 3 wherein said normalisation parameter is a combination of the parameters

24. A method according to claim 3 wherein said normalisation parameter is the product of

27. A computer program product adapted to carry out the steps of claim 3 when run on a computer.

30. A computer readable carrier medium comprising computer executable program code adapted to carry out the steps of claim 3.