Please use this identifier to cite or link to this item: https://doi.org/10.1109/TIP.2009.2017339
Title: Hierarchical segmentation-based image coding using hybrid quad-binary trees
Authors: Kassim, A.A. 
Lee, W.S. 
Zonoobi, D.
Keywords: Beamlets
Binary space-partitioning
Image coding
Platelets
Quadtrees
Segmentation
Wedgelets
Issue Date: 2009
Citation: Kassim, A.A., Lee, W.S., Zonoobi, D. (2009). Hierarchical segmentation-based image coding using hybrid quad-binary trees. IEEE Transactions on Image Processing 18 (6) : 1284-1291. ScholarBank@NUS Repository. https://doi.org/10.1109/TIP.2009.2017339
Abstract: A novel segmentation-based image approximation and coding technique is proposed. A hybrid quad-binary (QB) tree structure is utilized to efficiently model and code geometrical information within images. Compared to other tree-based representation such as wedgelets, the proposed QB-tree based method is more efficient for a wide range of contour features such as junctions, corners and ridges, especially at low bit rates. © 2009 IEEE.
Source Title: IEEE Transactions on Image Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/56184
ISSN: 10577149
DOI: 10.1109/TIP.2009.2017339
Appears in Collections:Staff Publications

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