- Research Article
- Open Access
Costs and Advantages of Object-Based Image Coding with Shape-Adaptive Wavelet Transform
EURASIP Journal on Image and Video Processing volume 2007, Article number: 078323 (2007)
Object-based image coding is drawing a great attention for the many opportunities it offers to high-level applications. In terms of rate-distortion performance, however, its value is still uncertain, because the gains provided by an accurate image segmentation are balanced by the inefficiency of coding objects of arbitrary shape, with losses that depend on both the coding scheme and the object geometry. This work aims at measuring rate-distortion costs and gains for a wavelet-based shape-adaptive encoder similar to the shape-adaptive texture coder adopted in MPEG-4. The analysis of the rate-distortion curves obtained in several experiments provides insight about what performance gains and losses can be expected in various operative conditions and shows the potential of such an approach for image coding.
Kunt M, Benard M, Leonardi R: Recent results in high-compression image coding. IEEE Transactions on Circuits and Systems 1987,34(11):1306-1336. 10.1109/TCS.1987.1086071
ISO/IEC JTC1 ISO/IEC 14496-2: coding of audio-visual objects April 2001
Madhavi M, Fowler JE: Unequal error protection of embedded multimedia objects for packet-erasure channels. Proceedings of the IEEE International Workshop on Multimedia Signal Processing, December 2002, St. Thomas, Virgin Islands, USA 61-64.
Gan T, Ma K-K: Weighted unequal error protection for transmitting scalable object-oriented images over packet-erasure networks. IEEE Transactions on Image Processing 2005,14(2):189-199. 10.1109/TIP.2004.840692
Fowler JE, Fox DN: Wavelet-based coding of three-dimensional oceanographic images around land masses. Proceedings of IEEE International Conference on Image Processing (ICIP '00), September 2000, Vancouver, BC, Canada 2: 431-434.
Taubman D: High performance scalable image compression with EBCOT. IEEE Transactions on Image Processing 2000,9(7):1158-1170. 10.1109/83.847830
Skodras A, Christopoulos C, Ebrahimi T: The JPEG2000 still image compression standard. IEEE Signal Processing Magazine 2001,18(5):36-58. 10.1109/79.952804
Xie G, Shen H: Highly scalable, low-complexity image coding using zeroblocks of wavelet coefficients. IEEE Transactions on Circuits and Systems for Video Technology 2005,15(6):762-770. 10.1109/TCSVT.2005.848311
Sun X, Foote J, Kimber D, Manjunath BS: Region of interest extraction and virtual camera control based on panoramic video capturing. IEEE Transactions on Multimedia 2005,7(5):981-990. 10.1109/TMM.2005.854388
Li S, Li W: Shape-adaptive discrete wavelet transforms for arbitrarily shaped visual object coding. IEEE Transactions on Circuits and Systems for Video Technology 2000,10(5):725-743. 10.1109/76.856450
Cagnazzo M, Poggi G, Verdoliva L, Zinicola A: Region-oriented compression of multispectral images by shape-adaptive wavelet transform and SPIHT. Proceedings of IEEE International Conference on Image Processing (ICIP '04), October 2004, Singapore 4: 2459-2462.
Kawanaka A, Algazi VR: Zerotree coding of wavelet coefficients for image data on arbitrarily shaped support. Proceedings of the Data Compression Conference (DCC '99), March 1999, Snowbird, Utah, USA 534.
Minami G, Xiong Z, Wang A, Mehrotra S: 3-D wavelet coding of video with arbitrary regions of support. IEEE Transactions on Circuits and Systems for Video Technology 2001,11(9):1063-1068. 10.1109/76.946523
Said A, Pearlman WA: A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on Circuits and Systems for Video Technology 1996,6(3):243-250. 10.1109/76.499834
Egger O, Fleury P, Ebrahimi T, Kunt M: High-performance compression of visual information-a tutorial review—I: still pictures. Proceedings of the IEEE 1999,87(6):976-1011. 10.1109/5.763312
Usevitch BE: A tutorial on modern lossy wavelet image compression: foundations of JPEG 2000. IEEE Signal Processing Magazine 2001,18(5):22-35. 10.1109/79.952803
Sikora T: Trends and perspectives in image and video coding. Proceedings of the IEEE 2005,93(1):6-17. 10.1109/JPROC.2004.839601
Tian J, Wells R Jr.: Embedded image coding using wavelet difference reduction. In Wavelet Image and Video Compression. Edited by: Topiwala P. Kluwer Academic, Norwell, Mass, USA; 1998:289-301.
Lu Z, Pearlman WA: Wavelet coding of video object by object-based SPECK algorithm. Proceedings of the 22nd Picture Coding Symposium (PCS '01), April 2001, Seoul, Korea 413-416.
Liu Z, Hua J, Xiong Z, Wu Q, Castleman K: Lossy-to-lossless ROI coding of chromosome images using modified SPIHT and EBCOT. Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI '02), July 2002, Washington, DC, USA 317-320.
Fowler JE: Shape-adaptive tarp coding. Proceedings of IEEE International Conference on Image Processing (ICIP '03), September 2003, Barcelona, Spain 1: 621-624.
Fowler JE: Shape-adaptive coding using binary set splitting with K-D trees. Proceedings of IEEE International Conference on Image Processing (ICIP '04), October 2004, Singapore 5: 1301-1304.
Prandoni P, Vetterli M: Approximation and compression of piecewise smooth functions. Philosophical Transactions: Mathematical, Physical and Engineering Sciences 1999,357(1760):2573-2591. 10.1098/rsta.1999.0449
Ratnakar V: RAPP: lossless image compression with runs of adaptive pixel patterns. Proceedings of the 32nd Asilomar Conference on Signals, Systems & Computers, November 1998, Pacific Grove, Calif, USA 2: 1251-1255.
Goyal VK: Theoretical foundations of transform coding. IEEE Signal Processing Magazine 2001,18(5):9-21. 10.1109/79.952802
Katto J, Yasuda Y: Performance evaluation of subband coding and optimization of its filter coefficients. Visual Communications and Image Processing, November 1991, Boston, Mass, USA, Proceedings of SPIE 1605: 95-106.
Usevitch BE: Optimal bit allocation for biorthogonal wavelet coding. Proceedings of the 6th Data Compression Conference (DCC '96), March-April 1996, Snowbird, Utah, USA 387-395.
Cagnazzo M, Poggi G, Verdoliva L: Costs and advantages of shape-adaptive wavelet transform for region-based image coding. Proceedings of IEEE International Conference on Image Processing (ICIP '05), September 2005, Genova, Italy 3: 197-200.
Cagnazzo M, Gaetano R, Poggi G, Verdoliva L: Region based compression of multispectral images by classified KLT. Proceedings of IEEE International Conference on Image Processing (ICIP '06), October 2006, Atlanta, Ga, USA
Fowler JE: QccPack: an open-source software library for quantization, compression, and coding. Applications of Digital Image Processing XXIII, July 2000, San Diego, Calif, USA, Proceedings of SPIE 4115: 294-301.
About this article
Cite this article
Cagnazzo, M., Parrilli, S., Poggi, G. et al. Costs and Advantages of Object-Based Image Coding with Shape-Adaptive Wavelet Transform. J Image Video Proc 2007, 078323 (2007). https://doi.org/10.1155/2007/78323
- Image Processing
- Pattern Recognition
- Computer Vision
- Image Segmentation
- Wavelet Transform