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Project: Peer Group Filtering and
Perceptual Color Quantization
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People
Y. Deng, Charles
Kenney, B.S. Manjunath
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In the first part of
this work, peer group filtering (PGF), a nonlinear algorithm for image
smoothing and impulse noise removal in color images is presented. The
algorithm replaces each image pixel with the weighted average of its peer
group members which are classified based on the color similarity of its
neighboring pixels. Results show that it effectively removes the noise and
smoothes the color images without blurring the edges and the details. In
the second part of the work, PGF is used as a preprocessing before color
quantization. Local statistics obtained after PGF are used as weights in
the quantization to suppress color clusters in the noisy regions, since
human perception is less sensitive to the differences in these areas. As a
result, very coarse quantization can be obtained while preserving the
color information in the original images. This can be useful for efficient
color indexing in the content based retrieval application. Also useful for
color image segmentation.
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Examples
Some results of PGF and color quantization are shown
here. These are the color images appeared in the proceeding paper. Icon
images (jpg) are shown on this page. Click on each image to see the
uncompressed full-resolution one (tiff).
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a)
small area of the original "baboon" image |

b) same area of the 5% corrupted image |

c) result of vector median filtering
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d)
result of Teager-operator
method |

e) result of peer group filtering. |
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(a) part of the original "baboon"
image
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(b) result of PGF
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(c) result of Gaussian filtering.
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(a) original "baboon" image (512x512)
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(b) result of PGF
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(c) result of quantization with 18 colors.
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"flower garden" video (352x240) |
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(a) original image
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(b) result of PGF
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(c) result of quantization with 13 colors. |
Publications
These materials are
presented to ensure timely dissemination of scholarly and technical
work. Copyright and all rights therein are retained by authors or by
other copyright holders. All persons copying this information are
expected to adhere to the terms and constraints invoked by each
authors copyright. In most cases, these works may not be reposted
without the explicit permission of the copyright holder.
C.Kenney, Y. Deng, B. S.Manjunath, G. Hewer,
"Peer group image enhancement," IEEE Transactions on Image Processing, vol.10, (no.2), IEEE, Feb. 2001. p.326-34.
[abstract]

Y. Deng, B. S. Manjunath, C. Kenney, M.S.Moore, H.Shin,
"
An efficient color representation for image retrieval," IEEE Transactions on Image Processing, vol.10, (no.1), IEEE, Jan. 2001. p.140-7. [abstract]

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Y. Deng, S.Kenney, M.S.Moore and
B. S.Manjunath,
"Peer group
filtering and perceptual color image quantization",
Proc. IEEE International Symposium on Circuits and Systems VLSI , (ISCAS'99), Orlando, FL, vol 4, pp.21-4 , June 1999.
[abstract]
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