Abstract
In this paper, we propose a generic hybrid oriented-transform and wavelet-based image representation for intra-band image coding. We instantiate for three popular directional transforms having similar powers of approximation but different redundancy factors. For each transform type, we design a compression scheme wherein we exploit intra-band coefficient dependencies. We show that our schemes outperform alternative approaches reported in literature. Moreover, on some images, we report that two of the proposed codec schemes outperform JPEG2000 by over 1dB. Finally, we investigate the trade-off between oversampling and sparsity and show that, at low rates, hybrid coding schemes with transform redundancy factors as high as 1.25 to 5.8 are capable in fact of outperforming JPEG2000 and its critically-sampled wavelets.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mallat, S.: A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 11, 674–693 (1989)
Vetterli, M.: Wavelets, approximation and compression. IEEE Signal Processing Magazine 18, 59–73 (2001)
Candès, E.J., Donoho, D.: Ridgelets: a key to higher-dimensional intermittency. Phil. Trans. R. Soc. Lond. A. 357, 2495–2509 (1999)
Candès, E.J., Donoho, D.: New Tight Frames of Curvelets and Optimal Representations of Objects with Piecewise C2 Singularities. Comm. Pure Appl. Math. 57, 219–266 (2004)
Do, M.N., Vetterli, M.: Contourlets. In: Welland, G.V. (ed.) Beyond Wavelets, Academic Press, London (2003)
Le Pennec, E., Mallat, S.: Sparse Geometric Image Representations with Bandelets. IEEE Transactions on Image Processing 14, 423–438 (2005)
Shapiro, J.M.: Embedded Image Coding Using Zerotrees of Wavelet Coefficients. IEEE Transactions on Signal Processing 41, 3445–3462 (1993)
Said, A., Pearlman, W.: A New Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees. IEEE Trans. on Circuits and Systems for Video Tech. 6, 243–250 (1996)
Munteanu, A., Cornelis, J., Van der Auwera, G., Cristea, P.: Wavelet Image Compression - The Quadtree Coding Approach. IEEE Transactions on Information Technology in Biomedicine 3, 176–185 (1999)
Pearlman, W.A., Islam, A., Nagaraj, N., Said, A.: Efficient, low-complexity image coding with a set-partitioning embedded block coder. IEEE Trans. Circuits and Systems for Video Technology 14, 1219–1235 (2004)
Taubman, D.: High Performance Scalable Image Compression with EBCOT. IEEE Transactions on Image Processing 9, 1158–1170 (2000)
Wu, X.: High-order context modeling and embedded conditional entropy coding of wavelet coefficients for image compression. In: Thirty-First Asilomar Conference on Signals, Systems & Computers, vol. 2, pp. 1378–1382 (1997)
Hsiang, S.-T., Woods, J.W.: Embedded image coding using zeroblocks of subband/wavelet coefficients and context modeling. In: ISCAS. IEEE International Symposium on Circuits and Systems, Geneva, Switzerland, vol. 3, pp. 662–665. IEEE, Los Alamitos (2000)
Chappelier, V., Guillemot, C., Marinkovic, S.: Image Coding with Iterated Contourlet and Wavelet Transforms. In: Proc. IEEE International Conf. on Image Processing, Singapore, pp. 3157–3160. IEEE Computer Society Press, Los Alamitos (2004)
Liu, Y., Nguyen, T.T., Oraintara, S.: Low Bit-Rate Image Coding Based on Pyramidal Directional Filter Banks. In: Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, Toulouse, France, IEEE, Los Alamitos (2006)
Eslami, R., Radha, H.: Wavelet-based Contourlet Coding using an SPIHT-like Algorithm. In: Proc. of Conference on Information Sciences and Systems, NJ, pp. 784–788 (2004)
Do, M.N., Vetterli, M.: The Contourlet Transform: an Efficient Directional Multiresolution Image Representation. IEEE Trans. Image Proc. 14, 2091–2106 (2005)
Lu, Y., Do, M.N.: Multidimensional Directional Filter Banks and Surfacelets. IEEE Trans. Image Processing (to appear)
Liu, J., Moulin, P.: Information-Theoretic Analysis of Interscale and Intrascale Dependencies between Image Wavelet Coefficients. IEEE Transactions on Image Processing 10, 1647–1658 (2001)
Po, D.D.-Y., Do, M.N.: Directional multiscale modeling of images using the contourlet transform. IEEE Transactions on Image Processing 15, 1610–1620 (2006)
Alecu, A., Munteanu, A., Pizurica, A., Philips, W., Cornelis, J., Schelkens, P.: Information-Theoretic Analysis of Dependencies between Curvelet Coefficients. In: IEEE International Conference on Image Processing (ICIP), Atlanta, GA, USA, pp. 1617–1620. IEEE, Los Alamitos (2006)
Taubman, D., Marcelin, M.W.: JPEG2000: Image Compression Fundamentals, Standards, and Practice. Kluwer Academic Publishers, Norwell, Massachusetts (2002)
Candès, E.J., Demanet, L., Donoho, D.L., Ying, L.: Fast Discrete Curvelet Transforms. Applied and Computational Mathematics, California Institute of Technology (2005)
Lu, Y., Do, M.N.: CRISP-Contourlets: a Critically Sampled Directional Multiresolution Image Representation. In: Proc. SPIE Conf. on Wavelet Applic. in Signal and Image Proc. X, San Diego, USA (2003)
Schelkens, P., Munteanu, A., Barbarien, J., Galca, M., Giro-Nieto, X., Cornelis, J.: Wavelet Coding of Volumetric Medical Datasets. IEEE Trans. on Medical Imag. 22, 441–458 (2003)
Munteanu, A.: Wavelet Image Coding and Multiscale Edge Detection: Algorithms and Applications. PhD Thesis. Vrije Universiteit Brussel, Brussels (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Alecu, A., Munteanu, A., Pižurica, A., Cornelis, J., Schelkens, P. (2007). On Hybrid Directional Transform-Based Intra-band Image Coding. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_95
Download citation
DOI: https://doi.org/10.1007/978-3-540-74607-2_95
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74606-5
Online ISBN: 978-3-540-74607-2
eBook Packages: Computer ScienceComputer Science (R0)