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An Improved ORNAM Representation of Gray Images
ZHENG Yunping 1 *,Mudar Sarem 2
1.School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006
2. School of Software Engineering, Huazhong University of Science and Technology, Wuhan 430074
*Correspondence author
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Funding: the Fundamental Research Funds for the Central Universities of China（No.No. 2011ZM0074）, the Natural Science Foundation of Guangdong Province of China（No.No. S2011040005815）, the Foundation for Distinguished Young Talents in Higher Education of Guangdong of China （No.No. LYM11015）, the Research Fund for the Doctoral Program of Higher Education of China（No.No. 20120172120036）
Opened online: 9 April 2013
Accepted by: none
Citation: ZHENG Yunping,Mudar Sarem.An Improved ORNAM Representation of Gray Images[OL]. [ 9 April 2013] http://en.paper.edu.cn/en_releasepaper/content/4534073
 
 
An efficient image representation can save space and facilitate the manipulation of the acquired images. Recently, we have presented an efficient gray image representation method by using the overlapping rectangular non-symmetry and anti-packing model and the extended Gouraud shading approach, which was called ORNAM representation. In order to further improve the reconstructed image quality and reduce the number of the homogeneous blocks of the ORNAM representation, in this paper, we propose an Improved ORNAM representation of gray images, which is called IORNAM representation. Compared with most of the up-to-date and the state-of-the-art hierarchical representation methods, the IORNAM representation is characterized by two properties. (1) It adopts a ratio parameter of the length and the width of a homogenous block to improve the reconstructed image quality. (2) It uses a new expansion method to anti-pack the subpatterns of gray images to further decrease the number of homogenous blocks, which is important for improving the compression ratios of image representation and reducing the complexities of many image manipulation algorithms. The experimental results presented in this paper demonstrate that (1) The IORNAM representation is able to achieve high representation efficiency for gray images. (2) The IORNAM representation outperforms most of the up-to-date and the state-of-the-art hierarchical representation methods of gray images.
Keywords:gray image representation; extended Gouraud shading approach; overlapping rectangular NAM (ORNAM); spatial data structures (SDS); S-Tree Coding (STC); spatial- and DCT-based (SDCT)
 
 
 

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