An improved ORNAM representation of grey images
by Yunping Zheng; Mudar Sarem
International Journal of Computational Science and Engineering (IJCSE), Vol. 17, No. 2, 2018

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.

Online publication date: Thu, 27-Sep-2018

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