Image analysis – Image enhancement or restoration – Edge or contour enhancement
Reexamination Certificate
1999-12-22
2004-05-04
Lee, Thomas D. (Department: 2624)
Image analysis
Image enhancement or restoration
Edge or contour enhancement
C358S521000
Reexamination Certificate
active
06731823
ABSTRACT:
FIELD OF THE INVENTION
The invention relates generally to the field of digital image processing and, more particularly, to a method for enhancing the edge contrast and texture of a digital image.
BACKGROUND OF THE INVENTION
Traditional methods of increasing the apparent sharpness of a digital image, such as the technique of unsharp masking, often produce unwanted artifacts at large transition edges in the image. For example, unsharp masking is often described by the equation:
Sproc=Sorg+B
(
Sorg
-
Sus
)
where Sproc represents the processed image signal in which the high frequency components have been amplified, Sorg represents the original image signal, Sus represents the unsharp image signal, typically a smoothed image signal obtained by filtering the original image, and B represents the high frequency emphasis coefficient.
The unsharp masking operation may be modeled as a linear system. Thus, the magnitude of any frequency in Sproc is directly dependent upon the magnitude of that frequency in the Sorg image signal. As a consequence of this superposition principle, large edges in the Sorg image signal will often display a ringing artifact in the Sproc signal when the desired level of high frequency enhancement has been performed in other areas of the Sproc signal. This ringing artifact appears as a light or dark outline around the large edge, and may be visually objectionable.
Many non-linear filters based on local statistics exist for the purposes of noise reduction, sharpening, and contrast adjustment. For example, the median filter is well known in the art. In this filter, typically implemented for noise reduction, each pixel is replaced with the median value of some surrounding neighborhood. This filtering process is generally very successful at removing impulse noise; however, the processed image appears slightly less sharp than the original.
Another example of a non-linear filter based on local statistics is local histogram equalization, referred to as adaptive histogram modification by William Pratt on pages 278-284 of the book
Digital Image Processing, Second Edition
, John Wiley & Sons, 1991. With this filter, the values of pixels are modified by the cumulative histogram of a local window. This technique effectively adjusts the contrast of each region of a digital image, effectively increasing the local contrast in some regions of the image, and decreasing the contrast in other regions. This technique does not intend to increase the apparent sharpness of any given region. Also, this technique does not ensure that the typical artifacts of ringing will not occur.
There exist many algorithms for sharpening the appearance of images without generating artifacts or enhancing the notability of noise. In U.S. Pat. No. 4,571,635, Mahmoodi and Nelson teach the method of deriving an emphasis coefficient B that is used to scale the high frequency information of the digital image depending upon the standard deviation of image pixel values in a local neighborhood. In addition, in U.S. Pat. No. 5,081,692, Kwon and Liang teach that the emphasis coefficient B is based upon a center weighted variance calculation. However, neither use separate strategies for texture and edge regions.
In U.S. Pat. No. 4,794,531, Morishita et al teaches a method of generating the unsharp image with a filter whose weights on neighboring pixels are based upon the absolute difference between the central pixel and the neighboring pixel. Morishita claims that this method effectively reduces artifacts seen at the edges of a sharpened image (as compared with traditional unsharp masking). However, the method of Morishita does not offer explicit control over the amount of edge reshaping.
Thus, there exists a need for an alternative method of manipulating a digital image in order to generate an image signal that appears to be sharper, or more in focus, while minimizing the ringing artifact that is evident with the unsharp masking technique.
SUMMARY OF THE INVENTION
It is an object of this invention to allow for independent control of the enhancement applied to detail, large edges, and noisy regions.
The present invention is directed to overcoming one or more of the problems set forth above. Briefly summarized, according to one aspect of the present invention, the invention resides in a method for enhancing a digital image channel comprised of a plurality of image pixels, particularly where the digital image channel is split into first and second signals, such as pedestal and texture signals, that substantially comprise the digital image channel. The method involves utilizing a predetermined tone scale conversion to enhance the digital image channel. Initially, image values are provided from the first signal, e.g., the pedestal signal, corresponding to image pixels from a region of the image. Then, a statistical characteristic of the image pixels in the region is identified, and the predetermined tone scale conversion is normalized for the statistical characteristic in order to generate a normalized tone scale conversion. The normalized tone scale conversion is then performed on a central pixel of the region in order to generate a first signal with enhanced image values; and the first signal with enhanced image values is combined with the second signal to generate an enhanced digital image channel.
The present invention has the advantage of controlling the value of the central pixel in the pedestal signal in accordance with a statistical characteristic of the region, e.g., driving the value of the central pixel either toward the local maximum or the local minimum of the region, except in the case where the central pixel is substantially midway between the local maximum and the local minimum. Consequently, edge transitions in the pedestal signal occur over a narrower range of pixels than in the input image, thus when combined with the texture signal generating an image signal that appears to be sharper, or more in focus, than the original image. Moreover, since the output of the tone scale conversion is modified by the statistical characteristic, e.g., bounded by the local maximum and the local minimum of the region, systematic overshoot and undershoot at an edge boundary is diminished and the ringing artifact is not as noticeable.
REFERENCES:
patent: 4571635 (1986-02-01), Mahmoodi et al.
patent: 4794531 (1988-12-01), Morishita et al.
patent: 5081692 (1992-01-01), Kwon et al.
Digital Image Processing, 2nded. William K. Pratt, John Wiley & Sons, New York 1991, pp. 278-284.
Gallagher Andrew C.
Gindele Edward B.
Brinich Stephen
Eastman Kodak Company
Lee Thomas D.
Woods David M.
LandOfFree
Method for enhancing the edge contrast of a digital image... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method for enhancing the edge contrast of a digital image..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method for enhancing the edge contrast of a digital image... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3221183