Digital image processing system and method for processing digital images

• US 20050123211A1
• Filed: 08/06/2004
• Published: 06/09/2005
• Est. Priority Date: 12/09/2003
• Status: Active Grant

• Current Assignee: Chinese University of Hong Kong
• Original Assignee: Chinese University of Hong Kong
• Inventors: Tang, Xiaoou, Chu, Hoi Chung, Ho, Ying Fai, Leung, Kwok Yiu, Wong, Kam Fai
• Granted Patent: US 7,382,928 B2
• Time in Patent Office: Days
• US Class Current: 382/254
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 5/90 Dynamic range modification of images or parts thereof
• CPC Class Codes: H04N 1/60 Colour correction or control H04N1/54 takes precedence
• CPC Class Codes: H04N 25/683 by defect estimation performed on the scene signal, e.g. real time or on the fly detection
• CPC Class Codes: H04N 9/646 for image enhancement, e.g. vertical detail restoration, cross-colour elimination, contour correction, chrominance trapping filters
• CPC Class Codes: H04N 9/68 for controlling the amplitude of colour signals, e.g. automatic chroma control circuits H04N9/71, H04N9/73 take precedence; camera processing pipelines for controlling the colour saturation of colour signals H04N23/86
• CPC Class Codes: H04N 9/69 for modifying the colour signals by gamma correction controlling camera response for colour signals H04N23/83
• CPC Class Codes: H04N 9/73 Colour balance circuits, e.g. white balance circuits or colour temperature control camera processing pipelines for colour balance H04N23/88

Abstract

Disclosed is an automatic digital image enhancement method, including: determining the defects existing in the image based on pixel values, such as pixel luminance values and pixel color values, of the input digital image, and making corrections based on the determination results. The method can process images of digital photos, digital videos and make enhancement on exposure and color of the images. The method disclosed can also improve quickly and apparently the visual quality and appearance of images.

Claims

1. A method for processing a digital image, comprising:

detecting pixel values of pixels in said digital image;

determining whether or not a defect exists in said digital image by comparing said pixel values with a predetermined value; and

correcting said defect by adjusting said pixel values, if the defect exists.

2. The method according to claim 1, wherein said pixel value is a luminance value, and said determining comprises:

determining whether or not the largest luminance value of said digital image is smaller than a predetermined value.

3. The method according to claim 2, wherein said pixel value is a pixel luminance value, and said correcting comprises:

correcting said digital image globally by brightening said digital image using a monotonic increasing transformation function based on the largest luminance value of said digital image.

4. The method according to claim 1, wherein said pixel value is a luminance value, and said determining comprises:

determining whether or not the smallest luminance value of said digital image is larger than a predetermined value.

5. The method according to claim 4, wherein said pixel value is a pixel luminance value, and said correcting comprises:

correcting said digital image globally by darkening said digital image using a monotonic increasing transformation function based on the smallest luminance value of said digital image.

6. The method according to claim 1, wherein said pixel value is a pixel color value, and said method comprises:

determining a color casting factor of pixels in a highlight region by a predetermined largest color value and a predetermined smallest pixel color value among the maximum values of red, green and blue histograms of the pixels of said digital image; and

transforming the color value of each of the pixels globally to a larger color value in accordance with the color casting factor in the highlight region.

7. The method according to claim 1, wherein said pixel value is a pixel color value, and said method comprises:

determining a color casting factor of pixels in a shadow region by a predetermined smallest color value and a predetermined largest color value among the minimum values of red, green and blue histograms of the pixels of the digital image; and

transforming the color value of each of the pixels globally to a smaller color value in accordance with the color casting factor in the shadow region.

8. The method according to claim 6, wherein said transforming is performed based on the following quotations, respectively:

R′

=Rmax+(BrightMax−

Rmax)×

CCBright
G′

=Gmax+(BrightMax−

Gmax)×

CCBright
B′

=Bmax+(BrightMax−

Bmax)×

CCBright

wherein;

Rmax, Gmax and Bmax are the largest color value in the red, green and blue color channels of the histograms of the image, respectively;

BrightMax is the maximum among Rmax, Gmax and Bmax;

CCBright is a color casting factor in highlight region of the image; and

R′

, G′

, and B′

are respectively a color value of Rmax, Gmax and Bmax color after processed.

9. The method according to claim 7, wherein said transforming is performed based on following quotations, respectively:

R′

=Rmin−

(Rmin−

DarkMin)×

CCDark
G′

=Gmin−

(Gmin−

DarkMin)×

CCDark
B′

=Bmin−

(Bmin−

DarkMin)×

CCDark

wherein;

Rmin, Gmin and Bmin are the smallest color value in the red, green and blue color channels of the histograms of the image, respectively;

DarkMin is the minimum among Rmin, Gmin and Bmin;

CCDark is a color casting factor in shadow region of the image; and

R′

, G′

, and B′

are respectively a color value of Rmin, Gmin and Bmin color after processed.

10. The method according to claim 9, further comprising:

transforming the color values of a pixel based on a weighted mean value of the luminance value of pixels within a predetermining distance adjacent to said pixel, using a corresponding nonlinear monotonic increasing transformation function which enhances the image details hidden in a shaded area with poor contrast adaptively.

11. The method according to claim 10, wherein said weighted mean value is determined by a low pass filter.

12. The method according to claim 11, wherein said weighted mean value is determined by:

scaling down said digital image from an original dimension to a predetermined dimension;

smoothing said digital image with a low pass filter;

scaling up said digital image to said original dimension to determine a luminance value of each current pixel; and

determining said weighted mean value based on the luminance value of each current pixel.

13. The method according to claim 12, further comprising dividing said image scaled down into corresponding rectangle blocks, and determining the pixel value of said image scaled down by taking the mean value of the pixel luminance value in said corresponding rectangle block.

14. The method according to claim 10, further comprising:

determining whether the blue color value of a pixel in the digital is more than the red and green color values; and

transforming the blue color value adaptively to be close to but more than the bigger one of the red and green color values.

15. The method according to claim 14, wherein said blue color value B of said pixel is corrected by the following formula:

B′

=B−

(B−

RGmax)×

(1−

RGmax/255)×

(1−

U),

wherein;

B is the blue color value in a pixel of the image;

RGmax is a larger one between the color value in the red and green color channels of a pixel of the image; and

U, 0≦

U≦

1, the degree of underexposure, a parameter to control the degree of the noise removal.

16. An image processing system for enhancing a digital image, comprising:

image defect detection means for detecting pixel values of the digital image to determine whether a defect exists in said image; and

image correction means for correcting said defect if the defect exists in the image.

17. The image processing system according to claim 16, wherein said image defect detection means comprises a detection module detecting luminance values of pixels in the digital image to determine whether the digital image is underexposed;

and said image correction means comprises a correction module correcting the underexposed image.

18. The image processing system according to claim 16, wherein said image defect detection means comprises a detection module detecting luminance values of pixels in the digital image to determine whether the digital image is overexposed;

and said image correction means comprises a correction module correcting the overexposed image.

19. The image processing system according to claim 16, wherein said image defect detection means comprises a detection module detecting color values of pixels in the digital image to determine whether a color-casting exists in the digital image;

and said image correction means comprises a correction module correcting the color-casting image; and

20. The image processing system according to claim 16, wherein said image defect detection means comprises a detection module detecting color values of pixels in the digital image to determine whether shaded details exist in the digital image;

and said image correction means comprises a correction module correcting the shaded details.

21. The image processing system according to claim 17, wherein the detection means further comprises a noise detection module to determine whether blue chunk noise exists in the image;

and the correction means further comprises a module to correct the blue chunk noise.

22. The image processing system according to claim 20, wherein said correction means further comprises a Gaussian filter to obtain a weighted mean value of the luminance values of pixels within a predetermined distance adjacent to a specific pixel.

23. An image processing system for enhancing a digital image, comprising:

a detection module configured to detect pixel values of pixels in said digital image and to determine whether or not a defect exists in said digital image by comparing said pixel values with a predetermined value; and

a correction module configured to correct said defect by adjusting said pixel values, if the defect exists.