IP Library › Granted Patent US 8,369,640
Granted Patent B2
US 8,369,640 · App. 12/458,855 · Granted Feb 5, 2013

Image processing for removing a noise component contained in an image

Inventor: Kenichi Ishiga (Yokohama, JP)
Assignee: Nikon Corporation
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Quick Facts
Patent No.
US 8,369,640
App. No.
12/458,855
Granted
Feb 5, 2013
Kind
B2
Abstract

An image processing method for removing a noise component contained in an original image, includes: separating an original image into a temporary noise-free image and a temporary noise component; extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image; determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component; extracting an actual noise component by excluding the fine edge component from the temporary noise component; and removing noise from the original image based upon the extracted actual noise component.

Claims (54)

1. An image processing method for removing a noise component contained in an original image, comprising:

separating an original image into a temporary noise-free image and a temporary noise component;

extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image;

determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component;

extracting an actual noise component by excluding the fine edge component from the temporary noise component; and

removing noise from the original image based upon the extracted actual noise component;

wherein a probability of the fine edge component being present in the temporary noise component is estimated to be higher when the level of the edge component is greater relative to a noise fluctuation index value determined uniquely in correspondence to the original image.

2. An image processing method according to claim 1 , wherein:

a mixing ratio with which the fine edge component is present is statistically estimated based upon a Gaussian distribution probability assuming a ratio of the edge component and the noise fluctuation index value as an argument.

3. An image processing method according to claim 2 , wherein:

the fine edge component is excluded through attenuation by multiplying the temporary noise component by the Gaussian distribution probability.

4. An image processing method for removing a noise component contained in an original image, comprising:

separating an original image into a temporary noise-free image and a temporary noise component;

extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image;

determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component;

extracting an actual noise component by excluding the fine edge component from the temporary noise component; and

removing noise from the original image based upon the extracted actual noise component;

wherein the original image is separated into the temporary noise-free image having undergone adaptive smoothing and the temporary noise component representing a residue thereof by setting a noise fluctuation index value determined uniquely in correspondence to the original image and comparing a signal fluctuation width detected in an original image structure with the noise fluctuation index value.

5. An image processing method according to claim 4 , wherein:

the temporary noise-free image having undergone adaptive smoothing is generated through weighted averaging of signal values at pixels near a target pixel, which fluctuate over a narrow range equal to or less than a range indicated by the noise fluctuation value, the weighted averaging being selectively executed according to a signal differential value; and

the temporary noise component is obtained by determining a difference between the temporary noise-free image and the original image.

6. An image processing method according to claim 4 , wherein:

the temporary noise component is extracted through a signal conversion processing phase in which only a component fluctuating over a small range equal to or less than a range indicated by the noise fluctuation index value in a differential signal representing a difference between the original image and a uniformly smooth image, is allowed to pass through; and

the temporary noise-free image is generated by subtracting the temporary noise component from the original image.

7. An image processing method for removing a noise component contained in an original image, comprising:

separating an original image into a temporary noise-free image and a temporary noise component;

extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image;

determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component;

extracting an actual noise component by excluding the fine edge component from the temporary noise component; and

removing noise from the original image based upon the extracted actual noise component;

wherein an image referencing range over which the edge detection is executed is set in correspondence to an image referencing range set for generation of the temporary noise-free image.

8. An image processing method for removing a noise component contained in an original image, comprising:

separating an original image into a temporary noise-free image and a temporary noise component;

extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image;

determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component;

extracting an actual noise component by excluding the fine edge component from the temporary noise component; and

removing noise from the original image based upon the extracted actual noise component;

wherein the original image is a band-limited subband image in multiresolution representation.

9. An image processing method for removing a noise component contained in an original image, comprising:

separating an original image into a temporary noise-free image and a temporary noise component;

extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image;

determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component;

extracting an actual noise component by excluding the fine edge component from the temporary noise component; and

removing noise from the original image based upon the extracted actual noise component;

wherein the original image is an original image expressed in an actual space.

10. An image processing method for removing a noise component contained in an original image, comprising:

separating an original image into a temporary noise-free image and a temporary noise component;

extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image;

determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component;

extracting an actual noise component by excluding the fine edge component from the temporary noise component; and

removing noise from the original image based upon the extracted actual noise component;

wherein processing on the original image is executed individually on a luminance plane and a chrominance plane.

11. An image processing method according to claim 1 , wherein:

a uniform index value is used as the noise fluctuation index value irrespective of a brightness level of the original image by converting the original image to an image in uniform noise space or an image in a uniform color•uniform noise space.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 24, 2009
From: ISHIGA, KENICHI
To: NIKON CORPORATION
Reel/Frame 023030/0553 →
Priority Claims (2)
JP 2007-024066 · Feb 2, 2007 · national
JP 2007-024067 · Feb 2, 2007 · national
Continuity (2)
Continuation PCTJP2008051652 · Feb 1, 2008
Related Publication 20090290067A1 · Nov 26, 2009