Method and system for enhancing digital images

Claim 3

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.

Claim 4

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.

Claim 5

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.

Claim 6

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.

Claim 7

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.

Claim 8

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.

Claim 9

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.

Claim 10

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.

Claim 11

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.

Claim 12

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.

Claim 13

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.

Claim 14

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.

Claim 15

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.

Claim 16

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.

Claim 19

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.

Claim 20

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.

Claim 21

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.

Claim 22

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.

Claim 23

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

Claim 26

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.

Claim 27

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.

Claim 28

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.

Claim 29

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.

Claim 30

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.

Claim 31

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.

Claim 32

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.

Claim 33

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.

Claim 34

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.

Claim 35

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.

Claim 36

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.

Claim 37

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.

Claim 38

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.

Claim 39

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.

Claim 40

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.

Claim 41

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.

Claim 42

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.

Claim 43

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.

Claim 44

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

Claim 47

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.

Claim 48

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.

Claim 49

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.

Claim 50

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.

Claim 51

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.

Claim 52

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.

Claim 53

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.

Claim 54

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.

Claim 55

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.

Claim 56

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.

Claim 57

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.

Claim 58

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.

Claim 59

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.

Claim 60

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.

Claim 61

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.

Claim 62

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.

Claim 63

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.

Claim 64

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.

Claim 65

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.

Claim 66

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.

Claim 67

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.

Claim 68

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.

Claim 69

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

Claim 70

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.

Claim 71

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.

Claim 72

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.

Claim 73

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.

Claim 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 low pass filter the at least one segment transform to produce the at least one filtered transform.

Claim 75

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.

Claim 76

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.

Claim 77

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.

Claim 78

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.

Claim 79

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.

Claim 80

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.

Claim 81

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.

Claim 82

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.

Claim 83

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.

Claim 84

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.

Claim 85

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.

Claim 86

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.

Claim 87

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.

Claim 88

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.

Claim 89

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.

Claim 90

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.

Claim 91

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.

Claim 92

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

Claim 93

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.

Claim 94

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.

Claim 95

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.

Claim 96

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.

Claim 97

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.

Claim 98

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.