Method and system for enhancing digital images

• US 6,771,833 B1
• Filed: 04/18/2000
• Issued: 08/03/2004
• Est. Priority Date: 08/20/1999
• Status: Expired due to Term

• Current Assignee: Monument Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Eastman Kodak Company
• Inventors: Edgar, Albert D.
• Primary Examiner(s): Mehta, Bhavesh M.
• Assistant Examiner(s): AZARIAN, SEYED H
• Application Number:
  US09/551,785
• Time in Patent Office: 1,568 Days
• Field of Search: 382/254, 382/250, 382/251, 382/255, 382/258, 382/260, 382/261, 382/262, 382/263, 382/264, 382/265, 382/266, 382/267, 382/256, 382/270, 382/274, 382/275, 358/1.9, 358/3.31, 358/3.27, 210/650, 348/607, 348/606, 348/609, 348/624, 348/618, 430/363
• US Class Current: 382/254
• CPC Class Codes: G06T 2207/10008 from scanner, fax or copier
• CPC Class Codes: G06T 2207/20056 Discrete and fast Fourier transform, [DFT, FFT]
• CPC Class Codes: G06T 2207/20204 Removing film grain; Adding simulated film grain
• CPC Class Codes: G06T 5/10 using non-spatial domain filtering
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

One aspect of the invention is a method of enhancing a digital image comprising at least one image channel. At least one spatial domain segment of a plurality of spatial domain segments of an image channel is transformed from the spatial domain to the frequency domain to create at least one segment transform. The spatial domain segment comprises one of a plurality of spatial domain segments of at least one image channel. At least one noise correction function is generated in response to the segment transform. The noise correction function may then be applied to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the segment transform. The corrected transform may be transformed from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

Claims

1. A method of enhancing a digital image comprising at least one image channel, comprising:

transforming at least one spatial domain segment of a plurality of spatial domain segments of the at least one image channel from the spatial domain to the frequency domain to create at least one segment transform, wherein each spatial domain segment comprises one of a plurality of spatial domain segments of the at least one image channel;

generating at least one noise correction function in response to the at least one segment transform, wherein the generating further comprises generating a plurality of cross correlation functions wherein a particular one of the plurality of cross correlations depends upon the cross correlation between a first segment transform derived from a first image channel and one or more spatially corresponding segment transforms from one or more image channels other than the first image channel of the digital image;

applying the at least one noise correction function to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the at least one segment transform; and

transforming the at least one corrected transform from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

2. The method of claim 1, further comprising:

normalizing the magnitude of the noise in the digital image to a constant value over all frequencies prior to the first transforming step.

3. The method of claim 1, wherein the generating step further comprises generating at least one filtered transform in response to the at least one segment transform.

4. The method of claim 3, wherein the generating step further comprises low pass filtering the at least one segment transform to produce the at least one filtered transform.

5. The method of claim 3, wherein the generating step further comprises low pass RMS filtering the at least one segment transform to produce the at least one filtered transform.

6. The method of claim 1 wherein the generating step further comprises frequency spreading the at least one segment transform to produce at least one spread transform.

7. The method of claim 6, wherein the generating step further comprises generating at least one estimate transform that depends upon the at least one spread transform and the at least one segment transform.

8. The method of claim 7, wherein the generating step further comprises creating at least one mask function operable to attenuate noise frequencies and accept image frequencies, the mask function generated in response to the at least one estimate transform.

9. The method of claim 8, wherein the generating step further comprises applying the at least one mask function to the at least one estimate transform to form the at least one noise correction function.

10. The method of claim 1, wherein the at least one noise correction function is applied such that a preselected residual level of noise remains in the at least one corrected spatial domain segment.

11. The method of claim 3, wherein the generating step further comprises frequency spreading the at least one filtered transform to produce at least one spread transform.

12. The method of claim 11, wherein the generating step further comprises generating at least one estimate transform that depends upon the at least one spread transform and the at least one filtered transform.

13. The method of claim 12, wherein the generating step further comprises creating at least one mask function operable to attenuate noise frequencies and accept image frequencies, the at least one mask function generated in response to the at least one estimate transform.

14. The method of claim 13, wherein the generating step further comprises applying the at least one mask function to the at least one estimate transform to form the at least one noise correction function.

15. The method of claim 14, wherein the at least one noise correction function is applied such that a preselected residual level of noise remains in the at least one corrected spatial domain segment.

17. The method of claim 1, wherein the generating step further comprises creating at least one segment estimate of noise compared to signal in the at least one spatial domain segment.

18. The method of claim 17, wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon, directly or indirectly, the at least one segment transform;

and wherein the generating step further comprises attenuating noise frequencies and accepting image frequencies based upon the at least one estimate of noise compared to signal.

19. The method of claim 18, wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon at least one filtered segment transform obtained by filtering the at least one segment transform.

20. The method of claim 19, wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon a frequency spread version of the at least one filtered segment transform.

21. The method of claim 1, wherein one or more of the plurality of spatial domain segments overlap.

16. A method of enhancing a digital image comprising at least one image channel, comprising:

transforming at least one spatial domain segment of a plurality of spatial domain segments of the at least one image channel from the spatial domain to the frequency domain to create at least one segment transform, wherein each spatial domain segment comprises one of a plurality of spatial domain segments of the at least one image channel;

generating at least one noise correction function in response to the at least one segment transform, wherein the generating further comprises;

generating at least one filtered transform in response to the at least one segment transform;

frequency spreading the at least one filtered transform to produce at least one spread transform;

generating at least one estimate transform that depends upon the at least one spread transform and the at least one filtered transform;

creating at least one mask function operable to attenuate noise frequencies and accept image frequencies, the at least one mask function generated in response to the at least one estimate transform;

applying the at least one mask function to the at least one estimate transform to form the at least one noise correction function; and

filtering at least one cross correlation to produce that at least one filtered transform, wherein the at least one cross correlation depends upon the cross correlation between the at least one segment transform and at least one spatially corresponding segment transform from an image channel of the digital image other than the at least one image channel;

applying the at least one noise correction function to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the at least one segment transform; and

transforming the at least one corrected transform from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

22. A method of enhancing a multicolor digital image comprising a plurality of color channels, comprising:

transforming each of a plurality of spatial domain segments of the color channels from the spatial domain to the frequency domain to create a plurality of segment transforms;

generating a plurality of noise correction functions in response to corresponding ones of the plurality of segment transforms, wherein the generating further comprises generating a plurality of cross correlation functions wherein a particular one of the plurality of cross correlations depends upon the cross correlation between a first segment transform derived from a first color channel and one or more spatially corresponding segment transforms from one or more color channels other than the first color channel of the multicolor digital image;

applying ones of the plurality of noise correction functions to produce a plurality of corrected transforms wherein each corrected transform depends upon, directly or indirectly, a corresponding segment transform; and

transforming ones of the plurality of corrected transforms from the frequency domain to the spatial domain to create a plurality of corrected spatial domain segments.

23. The method of claim 22 further comprising normalizing the magnitude of the noise in each of the plurality of color channels of the multicolor digital image to a constant value over all frequencies prior to the first transforming step.

24. The method of claim 22, wherein the generating step further comprises generating a plurality of filtered transforms in response to the plurality of segment transforms.

25. The method of claim 24 wherein the generating step further comprises low pass filtering ones of the plurality of segment transforms to produce the plurality of filtered transforms.

26. The method of claim 24, wherein the generating step further comprises low pass RMS filtering ones of the plurality of segment transforms to produce the plurality of filtered transforms.

27. The method of claim 22 wherein the generating step further comprises frequency spreading ones of the plurality of segment transforms to produce a plurality of spread transforms.

28. The method of claim 27 wherein the generating step further comprises generating a plurality of estimate transforms each dependent upon a corresponding one of the plurality of spread transforms and a corresponding one of the plurality of segment transforms.

29. The method of claim 28 wherein the generating step further comprises creating a plurality of mask functions operable to attenuate noise frequencies and accept image frequencies, each mask function generated in response to a corresponding one of the plurality of estimate transforms.

30. The method of claim 29 wherein the generating step further comprises applying ones of the plurality of mask functions to corresponding ones of the plurality of estimate transforms to form a plurality of noise correction functions.

31. The method of claim 30, wherein ones of the plurality of noise correction functions are applied such that a preselected residual level of noise remains in the corresponding ones of the plurality of corrected spatial domain segments.

32. The method of claim 24 wherein the generating step further comprises frequency spreading ones of the plurality of filtered transforms to produce a plurality of spread transforms.

33. The method of claim 32, wherein the generating step further comprises generating a plurality of estimate transforms wherein each of the plurality of estimate transforms depends upon a corresponding one of the plurality of spread transforms and a corresponding one of the plurality of filtered transforms.

34. The method of claim 33, wherein the generating step further comprises creating a plurality of mask functions operable to attenuate noise frequencies and accept image frequencies, wherein each of the plurality of mask functions is generated in response to a corresponding one of the plurality of estimate transforms.

35. The method of claim 34, wherein the generating step further comprises applying ones of the plurality of mask functions to corresponding ones of the plurality of estimate transforms to form the plurality of noise correction functions.

36. The method of claim 35 wherein ones of the plurality of noise correction functions are applied such that a preselected residual level of noise remains in corresponding ones of the plurality of corrected spatial domain segments.

37. The method of claim 22 wherein the generating step further comprises creating a segment estimate of noise compared to signal for each of the plurality of spatial domain segments.

38. The method of claim 37, wherein each segment estimate of noise compared to signal in each spatial domain segment depends upon, directly or indirectly, the corresponding one of the plurality of segment transforms;

and wherein the generating step further comprises attenuating noise frequencies and accepting image frequencies based upon each segment estimate of noise compared to signal.

39. The method of claim 38, wherein each segment estimate of noise compared to signal in each spatial domain segment depends upon a corresponding one of the plurality of filtered segment transforms obtained by filtering the corresponding one of the segment transforms.

40. The method of claim 39 wherein each segment estimate of noise compared to signal in the corresponding one of the plurality of spatial domain segments depends upon a frequency spread version of the corresponding one of the filtered segment transforms.

41. The method of claim 22 wherein one or more of the plurality of spatial domain segments overlap.

42. A method of enhancing a multicolor digital image comprising a plurality of color channels, comprising:

transforming each of a plurality of spatial domain segments of the color channels from the spatial domain to the frequency domain to create a plurality of segment transforms;

generating a plurality of noise correction functions in response to corresponding ones of the plurality of segment transforms, wherein the generating step further comprises;

frequency spreading ones of the plurality of segment transforms to produce a plurality of spread transforms;

generating a plurality of estimate transforms each dependent upon a corresponding one of the plurality of spread transforms and a corresponding one of the plurality of segment transforms;

creating a plurality of mask functions operable to attenuate noise frequencies and accept image frequencies, each mask function generated in response to a corresponding one of the plurality of estimate transforms;

applying ones of the plurality of mask functions to corresponding ones of the plurality of estimate transforms to form a plurality of noise correction functions; and

filtering at least one cross correlation to produce the at least one filtered transform, wherein the at least one cross correlation depends upon the cross correlation between at least one of the plurality of segment transforms and at least one spatially corresponding one of the plurality of segment transforms from a color channel of the digital image other than the color channel associated with the at least one of the plurality of segment transforms;

applying ones of the plurality of noise correction functions to produce a plurality of corrected transforms wherein each corrected transform depends upon, directly or indirectly, a corresponding segment transform; and

transforming ones of the plurality of corrected transforms from the frequency domain to the spatial domain to create a plurality of corrected spatial domain segments.

43. A digital image scanning system comprising:

scanning hardware operable to scan a photographic image and convert the photographic image into a digital image; and

computer software associated with the scanning hardware and operable to;

transform at least one spatial domain segment of a plurality of spatial domain segments of the at least one image channel from the spatial domain to the frequency domain to create at least one segment transform, wherein each spatial domain segment comprises one of a plurality of spatial domain segments of the at least one image channel;

generate at least one noise correction function in response to the at least one segment transform, wherein the generating further comprises generating a plurality of cross correlation functions wherein a particular one of the plurality of cross correlations depends upon the cross correlation between a first segment transform derived from a first image channel and one or more spatially corresponding segment transforms from one or more image channels other than the first image channel of the digital image;

apply the at least one noise correction function to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the at least one segment transform; and

transform the at least one corrected transform from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

44. The digital image scanning system of claim 43, wherein the computer software is further operable to:

normalize the magnitude of the noise in the digital image to a constant value over all frequencies prior to the first transforming step.

45. The digital image scanning system of claim 43, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to generate at least one filtered transform in response to the at least one segment transform.

46. The digital image scanning system of claim 45 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to low pass filter the at least one segment transform to produce the at least one filtered transform.

47. The digital image scanning system of claim 45 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to low pass RMS filter the at least one segment transform to produce the at least one filtered transform.

48. The digital image scanning system of claim 43 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to frequency spread the at least one segment transform to produce at least one spread transform.

49. The digital image scanning system of claim 48, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to generate at least one estimate transform that depends upon the at least one spread transform and the at least one segment transform.

50. The digital image scanning system of claim 49 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to create at least one mask function operable to attenuate noise frequencies and accept image frequencies, the mask function generated in response to the at least one estimate transform.

51. The digital image scanning system of claim 50 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to apply the at least one mask function to the at least one estimate transform to form the at least one noise correction function.

52. The digital image scanning system of claim 43, wherein the computer software is operable to apply the at least one noise correction function such that a preselected residual level of noise remains in the at least one corrected spatial domain segment.

53. The digital image scanning system of claim 45 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to frequency spread the at least one filtered transform to produce at least one spread transform.

54. The digital image scanning system of claim 53 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to generate at least one estimate transform that depends upon the at least one spread transform and the at least one filtered transform.

55. The digital image scanning system of claim 54 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to create at least one mask function operable to attenuate noise frequencies and accept image frequencies, the at least one mask function generated in response to the at least one estimate transform.

56. The digital image scanning system of claim 55, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to apply the at least one mask function to the at least one estimate transform to form the at least one noise correction function.

57. The digital image scanning system of claim 56 wherein the computer software is operable to apply the at least one noise correction function such that a preselected residual level of noise remains in the at least one corrected spatial domain segment.

59. The digital image scanning system of claim 43, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to create at least one segment estimate of noise compared to signal in the at least one spatial domain segment.

60. The digital image scanning system of claim 59 wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon, directly or indirectly, the at least one segment transform;

and wherein the computer software, in connection with the generation of at least one noise correction function is further operable to attenuate noise frequencies and accept image frequencies based upon the at least one estimate of noise compared to signal.

61. The digital image scanning system of claim 60 wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon at least one filtered segment transform obtained by filtering the at least one segment transform.

62. The digital image scanning system of claim 61 wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon a frequency spread version of the at least one filtered segment transform.

63. The digital image scanning system of claim 43 wherein one or more of the plurality of spatial domain segments overlap.

58. A digital image scanning system comprising:

scanning hardware operable to scan a photographic image and convert the photographic image into a digital image; and

computer software associated with the scanning hardware and operable to;

transform at least one spatial domain segment of a plurality of spatial domain segments of the at least one image channel from the spatial domain to the frequency domain to create at least one segment transform, wherein each spatial domain segment comprises one of a plurality of spatial domain segments of the at least one image channel;

generate at least one noise correction function in response to the at least one segment transform, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to;

generate at least one filtered transform in response to the at least one segment transform;

frequency spread the at least one filtered transform to produce at least one spread transform;

generate at least one estimate transform that depends upon the at least one spread transform and the at least one filtered transform;

create at least one mask function operable to attenuate noise frequencies and accept image frequencies, the at least one mask function generated in response to the at least one estimate transform;

apply the at least one mask function to the at least one estimate transform to form the at least one noise correction function, wherein the computer software is operable to apply the at least one noise correction function such that a preselected residual level of noise remains in the at least one corrected spatial domain segment; and

filter at least one cross correlation to produce the at least one filtered transform, wherein the at least one cross correlation depends upon the cross correlation between the at least one segment transform and at least one spatially corresponding segment transform from an image channel of the digital image other than the at least one image channel;

apply the at least one noise correction function to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the at least one segment transform; and

transform the at least one corrected transform from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

64. A digital image processing system comprising:

a computer readable storage medium; and

computer software stored on the computer readable storage medium and operable to;

transform at least one spatial domain segment of a plurality of spatial domain segments of the at least one image channel from the spatial domain to the frequency domain to create at least one segment transform, wherein each spatial domain segment comprises one of a plurality of spatial domain segments of the at least one image channel;

generate at least one noise correction function in response to the at least one segment transform, wherein the generating further comprises generating a plurality of cross correlation functions wherein a particular one of the plurality of cross correlations depends upon the cross correlation between a first segment transform derived from a first image channel and one or more spatially corresponding segment transforms from one or more image channels other than the first image channel of a digital image;

apply the at least one noise correction function to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the at least one segment transform; and

transform the at least one corrected transform from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

65. The digital image processing system of claim 64, wherein the computer software is further operable to:

normalize the magnitude of the noise in the digital image to a constant value over all frequencies prior to the first transforming step.

66. The digital image processing system of claim 64 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to generate at least one filtered transform in response to the at least one segment transform.

67. The digital image processing system of claim 66 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to low pass filter the at least one segment transform to produce the at least one filtered transform.

68. The digital image processing system of claim 66 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to low pass RMS filter the at least one segment transform to produce the at least one filtered transform.

69. The digital image processing system of claim 64, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to frequency spread the at least one segment transform to produce at least one spread transform.

70. The digital image processing system of claim 69, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to generate at least one estimate transform that depends upon the at least one spread transform and the at least one segment transform.

71. The digital image processing system of claim 70 wherein the computer software, in connection with the generation of at least one noise correction function is further operable to create at least one mask function operable to attenuate noise frequencies and accept image frequencies, the mask function generated in response to the at least one estimate transform.

72. The digital image processing system of claim 71, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to apply the at least one mask function to the at least one estimate transform to form the at least one noise correction function.

73. The digital image processing system of claim 64, wherein the computer software is operable to apply the at least one noise correction function such that a preselected residual level of noise remains in the at least one corrected spatial domain segment.

74. The digital image processing system of claim 66, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to frequency spread that at least one filtered transform to produce at least one spread transform.

75. The digital image processing system of claim 74, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to generate at least one estimate transform that depends upon the at least one spread transform and the at least one filtered transform.

76. The digital image processing system of claim 75, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to create at least one mask function operable to attenuate noise frequencies and accept image frequencies, the at least one mask function generated in response to the at least one estimate transform.

77. The digital image processing system of claim 76, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to apply the at least one mask function to the at least one estimate transform to form the at least one noise correction function.

78. The digital image processing system of claim 77, wherein the computer software is operable to apply the at least one noise correction function such that a preselected residual level of noise remains in the at least one corrected spatial domain segment.

80. The digital image processing system of claim 64, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to create at least one segment estimate of noise compared to signal in the at least one spatial domain segment.

81. The digital image processing system of claim 80, wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon, directly or indirectly, the at least one segment transform;

and wherein the computer software, in connection with the generation of at least one noise correction function is further operable to attenuate noise frequencies and accept image frequencies based upon the at least one estimate of noise compared to signal.

82. The digital image processing system of claim 81, wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon at least one filtered segment transform obtained by filtering the at least one segment transform.

83. The digital image processing system of claim 82, wherein the at least one segment estimate of noise compared to signal in the at least one spatial domain segment depends upon a frequency spread version of the at least one filtered segment transform.

84. The digital image processing system of claim 64, wherein one or more of the plurality of spatial domain segments overlap.

79. A digital image processing system comprising:

a computer readable storage medium; and

computer software stored on the computer readable storage medium and operable to;

transform at least one spatial domain segment of a plurality of spatial domain segments of the at least one image channel from the spatial domain to the frequency domain to create at least one segment transform, wherein each spatial domain segment comprises one of a plurality of spatial domain segments of the at least one image channel;

generate at least one noise correction function in response to the at least one segment transform, wherein the computer software, in connection with the generation of at least one noise correction function is further operable to;

generate at least one filtered transform in response to the at least one segment transform,

frequency spread that at least one filtered transform to produce at least one spread transform;

generate at least one estimate transform that depends upon the at least one spread transform and the at least one filtered transform;

create at least one mask function operable to attenuate noise frequencies and accept image frequencies, the at least one mask function generated in response to the at least one estimate transform;

apply the at least one mask function to the at least one estimate transform to form the at least one noise correction function, wherein the computer software is operable to apply the at least one noise correction function such that a preselected residual level of noise remains in the at least one corrected spatial domain segment; and

filter at least one cross correlation to produce the at least one filtered transform, wherein the at least one cross correlation depends upon the cross correlation between the at least one segment transform and at least one spatially corresponding segment transform from an image channel of the digital image other than the at least one image channel;

apply the at least one noise correction function to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the at least one segment transform; and

transform the at least one corrected transform from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

85. An altered digital image derived from a digital image comprising at least one image channel, comprising:

a computer readable storage medium; and

an altered digital image stored on the computer readable storage medium wherein the altered digital image was created by;

transforming at least one spatial domain segment of a plurality of spatial domain segments of the at least one image channel from the spatial domain to the frequency domain to create at least one segment transform, wherein each spatial domain segment comprises one of a plurality of spatial domain segments of the at least one image channel;

generating at least one noise correction function in response to the at least one segment transform, wherein the generating further comprises generating a plurality of cross correlation functions wherein a particular one of the plurality of cross correlations depends upon the cross correlation between a first segment transform derived from a first image channel and one or more spatially corresponding segment transforms from one or more image channels other than the first image channel of the digital image;

applying the at least one noise correction function to produce at least one corrected transform wherein the corrected transform depends upon, directly or indirectly, the at least one segment transform; and

transforming the at least one corrected transform from the frequency domain to the spatial domain to create at least one corrected spatial domain segment.

86. The altered digital image of claim 85, wherein the altered digital image was further created by normalizing the magnitude of the noise in the digital image to a constant value over all frequencies prior to the first transforming step.

87. The altered digital image of claim 85, wherein the generating step further comprises generating at least one filtered transform in response to the at least one segment transform.

88. The altered digital image of claim 85, wherein the generating step further comprises frequency spreading the at least one segment transform to produce at least one spread transform.

89. The altered digital image of claim 85, wherein the generating step further comprises creating at least one segment estimate of noise compared to signal in the at least one spatial domain segment.