IEICE TRANSACTIONS on Fundamentals
Image Contour Clustering by Vector Quantization on Multiscale Gradient Planes and Its Application to Image Coding
Summary :
We introduce an image contour clustering method based on a multiscale image representation and its application to image compression. Multiscale gradient planes are obtained from the mean squared sum of 2D wavelet transform of an image. The decay on the multiscale gradient planes across scales depends on the Lipshitz exponent. Since the Lipshitz exponent indicates the spatial differentiability of an image, the multiscale gradient planes represent smoothness or sharpness around edges on image contours. We apply vector quatization to the multiscale gradient planes at contours, and cluster the contours in terms of represntative vectors in VQ. Since the multiscale gradient planes indicate the Lipshitz exponents, the image contours are clustered according to its gradients and Lipshitz exponents. Moreover, we present an image recovery algorithm to the multiscale gradient planes, and we achieve the skech-based image compression by the vector quantization on the multiscale gradient planes.
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- IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.8 pp.1652-1660
- Publication Date
- 1998/08/25
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- Special Section PAPER (Special Section on Digital Signal Processing)
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Makoto NAKASHIZUKA, Yuji HIURA, Hisakazu KIKUCHI, Ikuo ISHII, "Image Contour Clustering by Vector Quantization on Multiscale Gradient Planes and Its Application to Image Coding" in IEICE TRANSACTIONS on Fundamentals,
vol. E81-A, no. 8, pp. 1652-1660, August 1998, doi: .
Abstract: We introduce an image contour clustering method based on a multiscale image representation and its application to image compression. Multiscale gradient planes are obtained from the mean squared sum of 2D wavelet transform of an image. The decay on the multiscale gradient planes across scales depends on the Lipshitz exponent. Since the Lipshitz exponent indicates the spatial differentiability of an image, the multiscale gradient planes represent smoothness or sharpness around edges on image contours. We apply vector quatization to the multiscale gradient planes at contours, and cluster the contours in terms of represntative vectors in VQ. Since the multiscale gradient planes indicate the Lipshitz exponents, the image contours are clustered according to its gradients and Lipshitz exponents. Moreover, we present an image recovery algorithm to the multiscale gradient planes, and we achieve the skech-based image compression by the vector quantization on the multiscale gradient planes.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_8_1652/_p
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@ARTICLE{e81-a_8_1652,
author={Makoto NAKASHIZUKA, Yuji HIURA, Hisakazu KIKUCHI, Ikuo ISHII, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Image Contour Clustering by Vector Quantization on Multiscale Gradient Planes and Its Application to Image Coding},
year={1998},
volume={E81-A},
number={8},
pages={1652-1660},
abstract={We introduce an image contour clustering method based on a multiscale image representation and its application to image compression. Multiscale gradient planes are obtained from the mean squared sum of 2D wavelet transform of an image. The decay on the multiscale gradient planes across scales depends on the Lipshitz exponent. Since the Lipshitz exponent indicates the spatial differentiability of an image, the multiscale gradient planes represent smoothness or sharpness around edges on image contours. We apply vector quatization to the multiscale gradient planes at contours, and cluster the contours in terms of represntative vectors in VQ. Since the multiscale gradient planes indicate the Lipshitz exponents, the image contours are clustered according to its gradients and Lipshitz exponents. Moreover, we present an image recovery algorithm to the multiscale gradient planes, and we achieve the skech-based image compression by the vector quantization on the multiscale gradient planes.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Image Contour Clustering by Vector Quantization on Multiscale Gradient Planes and Its Application to Image Coding
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1652
EP - 1660
AU - Makoto NAKASHIZUKA
AU - Yuji HIURA
AU - Hisakazu KIKUCHI
AU - Ikuo ISHII
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 1998
AB - We introduce an image contour clustering method based on a multiscale image representation and its application to image compression. Multiscale gradient planes are obtained from the mean squared sum of 2D wavelet transform of an image. The decay on the multiscale gradient planes across scales depends on the Lipshitz exponent. Since the Lipshitz exponent indicates the spatial differentiability of an image, the multiscale gradient planes represent smoothness or sharpness around edges on image contours. We apply vector quatization to the multiscale gradient planes at contours, and cluster the contours in terms of represntative vectors in VQ. Since the multiscale gradient planes indicate the Lipshitz exponents, the image contours are clustered according to its gradients and Lipshitz exponents. Moreover, we present an image recovery algorithm to the multiscale gradient planes, and we achieve the skech-based image compression by the vector quantization on the multiscale gradient planes.
ER -
English
