Boots – shoes – and leggings
Patent
1989-10-12
1991-04-23
Dixon, Joseph L.
Boots, shoes, and leggings
358166, 358167, 382 51, H03F 126
Patent
active
050105043
DESCRIPTION:
BRIEF SUMMARY
TECHNICAL FIELD OF THE INVENTION
The invention relates to block transform digital image processing methods for reducing noise in a digital image.
BACKGROUND OF THE INVENTION
U.S. Pat. No. 4,553,165, issued Nov. 12, 1985 to Bayer discloses a block transform image processing method for removing noise (such as film grain noise) from a digital image, produced for example by scanning a photographic image. According to the method disclosed by Bayer, the digital image is divided into blocks. Each block is transformed, for example by Walsh Hadamard transformation, to yield blocks of transform coefficients. The transform coefficients are modified in a nonlinear manner to reduce the noise in the image block, and the blocks of modified coefficients are inversely transformed to yield the processed image having reduced noise. The effect of this processing is to reduce the appearance of noise in the processed image while avoiding the introduction of an artifact caused by other prior art noise reduction processes in which false "edges" would appear in smooth areas of the the processed image (such as facial features).
While the technique disclosed by Bayer is indeed effective to avoid the appearance of false edges, while reducing the appearance of noise in the processed image, extensive testing by the present inventors of the image processing method employing the Walsh-Hadamard transformation has revealed the presence of another class of undesirable artifacts in the processed images that is not effectively avoided by the Walsh-Hadamard block transformation noise reduction method. These artifacts occur in areas of the image having fine texture, whereby the texture is replaced by smooth appearing areas. This artifact is particularly noticeable and objectionable in such image features as grass, hair, and textile patterns such as carpet. Careful investigation has also shown that the Bayer method somewhat reduces the sharpness of edge detail.
SUMMARY OF THE INVENTION
It is therefore the object of the present invention to provide a block transform image processing method that avoids the shortcomings noted above. In arriving at the present invention, we found it helpful to consider the statistical properties of the noise being removed from an image, and the statistical properties of the image details such as texure and edges that were to be preserved in the processed image. In particular, we examined the statistical properties of the noise and image detail in the transformed coordinate space. For a spatial transformation of the Walsh-Hadamard type, a transform coefficient of the noise is characterized by a generally Gaussian distribution around a mean value of zero. This is shown by Curve 10 in FIG. 2. The transform coefficients of the picture detail, including edges and texture, form a generally Lapacian distribution, also centered about zero (shown by Curve 12 in FIG. 2.)
The transform coefficients from the picture detail have generally higher amplitude in absolute terms than the ones From the noise. Noise suppression is achieved by thresholding the transform coefficients or by modifying them through a non linear gain function. This will remove most of the noise but unfortunately it will remove the low amplitude transform coefficients from the image detail which will create artifacts. The artifacts are most noticeable and objectionable in low contrast, fine textured area.
We also examined the variance distributions of the image components such as noise, texture, and edges, and noted that there was a much better separation of the statistics of the image components when plotted against variance of small regions. FIG. 3 is a graph showing variance plotted against distribution (number of occurrances) for film grain noise (Curve 1), texture (Curve 16), and edge detail (Curve 18) for a typical digital image produced by scanning a photograph.
It will be appreciated from a comparison of FIG. 2 with FIG. 3, that a noise reduction technique that discriminates based upon the variances of image detail will have a much better chance
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Kwon Hee-min
Lee Hsien-Che
Lee Hui-Jung
Liang Jeanine
Close Thomas H.
Dixon Joseph L.
Eastman Kodak Company
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