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总览 评价 郑运平 1，* ， Mudar Sarem 2， （ 1、 华南理工大学计算机科学与工程学院，广州 510006； 2、 华中科技大学，软件学院，武汉 430074； ） 摘要： 通过使用非对称逆布局模型和坐标编码程序，提出了一种新的的二值图像表示算法，简称为NAMCEP表示
郑运平1，*， Mudar Sarem2，
（
1、华南理工大学计算机科学与工程学院，广州 510006； 2、华中科技大学，软件学院，武汉 430074； ）
摘要：
通过使用非对称逆布局模型和坐标编码程序，提出了一种新的的二值图像表示算法，简称为NAMCEP表示算法。以图像处理里惯用的标准二值图像作为典型测试对象，实验结果表明：与流行的线性四元树(LQT) 和二元树 (Bintree)表示算法相比，NAMCEP表示算法不仅能分别减少75.99%和68.22%的结点数，而且还能分别节约422.44%和163.62%的存储空间。因此，NAMCEP表示是一种更为有效的二值图像表示算法。作为NAMCEP表示算法的一个应用，提出了一种基于NAMCEP的二值图像的面积计算方法。实验结果表明：基于NAMCEP表示的面积计算的平均执行速度比基于LQT表示和Bintree表示的平均执行速度分别提高了71.92%和65.91%，效果是非常明显的。因此，与基于LQT表示和Bintree表示的图像的面积计算算法相比，基于NAMCEP表示的计算算法能显著提高图像面积的计算速度。
关键词：
图像表示；二值图像；线性四元树；二元树；非对称逆布局模型；坐标编码程序；面积计算
ZHENG Yunping1,*， Mudar Sarem2,
（
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； ）
Abstract：
In this paper, we propose a novel binary image representation algorithm by using the Non-symmetry and Anti-packing Model (NAM) and the Coordinate Encoding Procedure, which is called NAMCEP. By taking some idiomatic standard binary images in the field of image processing as typical test objects, and by comparing our proposed NAMCEP representation with the linear quadtree (LQT) representation and the binary tree (Bintree) representation, the experimental results presented in this paper show that the NAMCEP can not only reduce the average node numbers by 75.99% and 68.22% than the LQT and the Bintree, respectively, but also can simultaneously improve the average compression ratios by 422.44% and 163.62% than the LQT and the Bintree, respectively. Therefore, our proposed NAMCEP representation algorithm of binary images is much more effective than the LQT and the Bintree representation algorithms. As an application of the NAMCEP representation, we also present a novel NAMCEP-based algorithm for area calculating. The experimental results presented in this paper also show that the average executing time improvement ratio for area calculating of the proposed NAMCEP representation over that of the LQT representation and the Bintree representation is 71.92% and 65.91%, respectively. Therefore, our proposed NAMCEP-based algorithm for area calculating is much faster than the LQT-based algorithm and the Bintree-based algorithm for area calculating.
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