2024-03-29T05:26:48Z
https://niigata-u.repo.nii.ac.jp/oai
oai:niigata-u.repo.nii.ac.jp:00001900
2022-12-15T03:34:42Z
423:424:425
453:454
Image Contour Clustering by Vector Quantization on Multiscale Gradient Planes and Its Application to Image Coding
Image Contour Clustering by Vector Quantization on Multiscale Gradient Planes and Its Application to Image Coding
Nakashizuka, Makoto
Hiura, Yuji
Kikuchi, Hisakazu
Ishii, Ikuo
copyright©1998 IEICE
sketch-based image coding
contour detection
image recovery
wavelet transform
multiscale analysis
vector quantization
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.
The Institute of Electronics, Information and Communication Engineers
1998-08
eng
journal article
http://hdl.handle.net/10191/6491
https://niigata-u.repo.nii.ac.jp/records/1900
http://www.ieice.org/jpn/trans_online/
AA10826239
09168508
IEICE transactions on fundamentals of electronics, communications and computer sciences
IEICE transactions on fundamentals of electronics, communications and computer sciences
E81-A
8
1652
1660
https://niigata-u.repo.nii.ac.jp/record/1900/files/e81-a_8_1652.pdf
application/pdf
1.2 MB
2019-07-29