Abstract
In this paper we analyze a method for classifying images which have been compressed using a biorthogonal wavelet transformation. The goal is to formulate a pattern recognition algorithm over a wavelet-compressed image set without requiring that the image set be decompressed. This paper extends previous work [8] which studies how to recognize objects in images compressed using orthogonal transforms, as in the JPEG/MPEG compression standards.
We gratefully acknowledge support from the National Science Foundation (grant number IRI-9308415)
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
A. Cohen, I. Daubechies, and J.-C. Feauveau. Biorthogonal bases of compactly supported wavelets. Comm. Pure Appl. Math., 45:485–560, 1992.
I. Daubechies. Orthogonal bases of compactly supported wavelets. Comm. Pure Appl. Math., 41:909–996, 1988.
G. Golub and C. Van Loan. Matrix Computation. The John Hopkins University Press, 1984.
R.C. Gonzales and R.E. Woods. Digital Image Processing. Addison-Wesley, 1993.
R.A. Horn and C.R. Johnson. Topics in Matrix Analysis. Cambridge University Press, 1991.
W. Hu and W. B. Seales. Biorthogonal wavelets and object recognition in the compressed domain. Technical report, Computer Science Dept., University of Kentucky, Lexington, Kentucky, 1997.
S. Mallat. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. Pattern Analysis and Machine Intelligence, 11:674–693, 1989.
W.B. Seales, M.D. Cutts, C.J. Yuan, and W. Hu. Object recognition in compressed imagery. Image and Vision Computing, to appear, 1998.
E.P. Simoncelli and E. H. Adelson. Efficient pyramid image coder (epic), 1996. Distribution available from ftp://ftp.cis.uppen.edu/pub/eero/epic.tar.Z. *** DIRECT SUPPORT *** A0008188 00013
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hu, W., Seales, W.B. (1997). Recognition in wavelet-compressed imagery. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63930-6_142
Download citation
DOI: https://doi.org/10.1007/3-540-63930-6_142
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63930-5
Online ISBN: 978-3-540-69669-8
eBook Packages: Springer Book Archive