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An improved gray image representation using overlapping rectangular non-symmetry and anti-packing and extended shading approach

机译:使用重叠矩形非对称,反打包和扩展阴影方法的改进的灰度图像表示

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Recently, we put forward a gray image representation method based on the overlapping rectangular non-symmetry and anti-packing model and the extended Gouraud shading approach, which was called ORNAM representation. Aiming at improving the reconstructed image quality of the ORNAM representation, in this paper, we propose an improved ORNAM representation, which is called the IORNAM representation, adopting a ratio control parameter of the length and the width of a homogenous block. The experimental results show that our proposed IORNAM representation can improve the reconstructed image quality by adopting the proposed ratio parameter and that the proposed IORNAM representation has about 15.15% and 143.64% storage-saving improvement ratio in average, respectively, when compared to the ORNAM representation and the STC representation, whereas maintaining the satisfactory image quality. What's more important, the IORNAM representation can also decrease the homogenous block number by 14.75% and 31.41% than the ORNAM representation and the STC representation, respectively.
机译:最近,我们提出了一种基于重叠矩形非对称和反打包模型以及扩展的Gouraud阴影方法的灰度图像表示方法,称为ORNAM表示。为了提高ORNAM表示的重建图像质量,在本文中,我们提出了一种改进的ORNAM表示,称为IORNAM表示,采用了均匀块的长度和宽度的比率控制参数。实验结果表明,我们提出的IORNAM表示可以通过采用建议的比率参数来改善重建的图像质量,并且与ORNAM表示相比,提出的IORNAM表示平均分别具有约15.15%和143.64%的存储节省改进率。和STC表示,同时保持令人满意的图像质量。更重要的是,IORNAM表示也可以分别比ORNAM表示和STC表示减少均匀块数14.75%和31.41%。

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