Abstract
Many applications like image compression requires sparse representation of image. To represent the image by sparse coefficients of transform is an old age technique. Still research is going on for better sparse representation of an image. A very recent technique is based on learning the basis for getting sparse coefficients. But learned basis are not guaranteed to span l 2 space, which is required for reconstruction. In this paper we are presenting a new technique to choose steerable basis of wavelet pyramid which gives sparse coefficients and better reconstruction. Here selection of steerable basis is based on clues from Hough transform.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Tropp, J.A., Laska, J.N., Duarte, M.F., Romberg, J.K., Baraniuk, R.G.: Beyond nyquist: Efficient sampling of sparse bandlimited signals. CoRR (2009)
Li, Y., Cichocki, A., ichi Amari, S., Shishkin, S., Cao, J., Gu, F., Cao, J., Gu, F.: Sparse representation and its applications in blind source separation. In: Seventeenth Annual Conference on Neural Information Processing Systems, NIPS 2003 (2003)
Sallee, P., Olshausen, B.A., Lewicki, M.S.: Learning sparse image codes using a wavelet pyramid architecture  13, 887–893 (2001)
Freeman, W.T., Edward, H.A.Y.: The design and use of steerable filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 13, 891–906 (1991)
Karasaridis, A., Simoncelli, E.: A filter design technique for steerable pyramid image transforms, pp. 2387–2390 (1996)
Duda, R.O., Hart, P.E.: Use of the hough transformation to detect lines and curves in pictures. Commun. ACM 15, 11–15 (1972)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bhavsar, J.K., Mitra, S.K. (2009). Deriving Sparse Coefficients of Wavelet Pyramid Taking Clues from Hough Transform. In: Chaudhury, S., Mitra, S., Murthy, C.A., Sastry, P.S., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2009. Lecture Notes in Computer Science, vol 5909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11164-8_53
Download citation
DOI: https://doi.org/10.1007/978-3-642-11164-8_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11163-1
Online ISBN: 978-3-642-11164-8
eBook Packages: Computer ScienceComputer Science (R0)