Article: An improved ORNAM representation of grey images Journal: International Journal of Computational Science and Engineering (IJCSE) 2018 Vol.17 No.2 pp.234 - 243 Abstract: An efficient image representation can save space and facilitate the manipulation of the acquired images. In order to further enhance the reconstructed image quality and reduce the number of the homogeneous blocks of the overlapping rectangular non-symmetry and anti-packing model (ORNAM) representation, in this paper, we propose an improved overlapping rectangular non-symmetry and anti-packing model representation (IORNAM) of grey images. Compared with most of the up-to-date and the state-of-the-art hierarchical representation methods, the new IORNAM representation is characterised 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 grey 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 new IORNAM representation is able to achieve high representation efficiency for grey images; 2) the new IORNAM representation outperforms most of the up-to-date and the state-of-the-art hierarchical representation methods of grey images. Inderscience Publishers - linking academia, business and industry through research

Title: An improved ORNAM representation of grey images

Authors: Yunping Zheng; Mudar Sarem

Addresses: School of Computer Science and Engineering, South China University of Technology, Guangzhou, China; Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, USA ' School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China

Abstract: An efficient image representation can save space and facilitate the manipulation of the acquired images. In order to further enhance the reconstructed image quality and reduce the number of the homogeneous blocks of the overlapping rectangular non-symmetry and anti-packing model (ORNAM) representation, in this paper, we propose an improved overlapping rectangular non-symmetry and anti-packing model representation (IORNAM) of grey images. Compared with most of the up-to-date and the state-of-the-art hierarchical representation methods, the new IORNAM representation is characterised 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 grey 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 new IORNAM representation is able to achieve high representation efficiency for grey images; 2) the new IORNAM representation outperforms most of the up-to-date and the state-of-the-art hierarchical representation methods of grey images.

Keywords: grey image representation; spatial- and DCT-based; SDCT; extended Gouraud shading approach; overlapping rectangular NAM; ORNAM; spatial data structures; SDS; S-tree coding; STC.

DOI: 10.1504/IJCSE.2018.094923

International Journal of Computational Science and Engineering, 2018 Vol.17 No.2, pp.234 - 243

Received: 04 Dec 2015
Accepted: 14 Feb 2016
Published online: 27 Sep 2018 *

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Title: An improved ORNAM representation of grey images

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