Abstract
This paper presents a new wavelet-based image contour coding technique, suitable for representing either shapes or generic contour maps. Starting from a contour map (e.g. a segmentation map or the result of an edge detector process), a unique one-dimensional signal is generated from the set of contour points. Coordinate jumps between contour extremities when under a tolerance threshold represent signal discontinuities but they can still be compactly coded in the wavelet domain. Exceeding threshold discontinuities are coded as side information. This side information and the amount of remaining discontinuity are minimized by an optimized contour segment sequencing. The obtained 1D signal is decomposed and coded in the wavelet domain by using a 1D extension of the SPIHT algorithm. The described technique can efficiently code any kind of 2D contour map, from one to many unconnected contour segments. It guarantees a fully embedded progressive coding, state-of-art coding performance, good approximation capabilities for both open and closed contours, and graceful visual degradation at low bit-rates.
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Zahn, C.T., Roskies, R.Z.: FourierDescriptorsforPlaneClosedCurves. IEEE Trans.Computers 21(3), 269–281 (1972)
Lee, S., Cho, D., Cho, Y., Son, S., Jang, E., Shin, J., Seo, Y.: Binary Shape Coding Using Baseline-Based Method. IEEE Trans. Circ. and Sys. for VideoTechnol. 9(1), 44–58 (1999)
O’Connell, K.J.: Object-adaptive vertex-based shape coding method. IEEE Trans. Circ. and Sys. for Video Technol. 7, 251–255 (1997)
Yamaguchi, N., Ida, T., Watanabe, T.: Abinary shape coding method using modified MMR. In: In:Proc. of Int. Conf. on Image Proc., pp. 504–508 (1997)
Brady, N., Bossen, F., Murphy, N.: Context-based arithmetic encoding of 2D shape sequences. In: Proc. of Int. Conf. on Image Proc., pp. 29–32 (1997)
Said, A., Pearlman, W.A.: A new, fast, and efficient image code based on Set Partitioning in Hierarchical Trees. IEEE Trans. Circ. and Sys. for Video Technol. 6(3), 243–250 (1996)
Signoroni, A., Arrigoni, M., Lazzaroni, F., Leonardi, R.: Improving SPIHT-based compression of volumetric medical data. In: Proc. of Picture Coding Symp., pp. 187–190 (2001)
Katsaggelos, A.K., Kondi, L.P., Meier, F.W., Ostermann, J., Schuster, G.M.: MPEG-4 and rate-distortion-based shape-coding techniques. Proceedings of the IEEE 86(6), 1126–1154 (1998)
Canny, J.: A computational approach to edge detection. IEEE Trans. on Pattern Anal. and Machine Intell. 8(6), 679–698 (1986)
Eden, M., Kocher, M.: On the performance of a contour coding algorithm in the contex to image coding-Part I: Contour segment coding. Signal Processing 8, 381–386 (1985)
Kuhn, M.: JBIGKIT lossless image compression library, http://www.cl.cam.ac.uk/~mgk25/jbigkit/
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© 2006 Springer-Verlag Berlin Heidelberg
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Adami, N., Gallina, P., Leonardi, R., Signoroni, A. (2006). Progressive Contour Coding in the Wavelet Domain. In: Atzori, L., Giusto, D.D., Leonardi, R., Pereira, F. (eds) Visual Content Processing and Representation. VLBV 2005. Lecture Notes in Computer Science, vol 3893. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11738695_24
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DOI: https://doi.org/10.1007/11738695_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33578-8
Online ISBN: 978-3-540-33579-5
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