一种基于可重叠RNAM的灰度图像表示算法  

Gray Image Representation Algorithm Based on Overlapping RNAM

作　　者：郑运平[1] 陈传波[2] 李祖嘉[1] 

机构地区：[1]华南理工大学计算机科学与工程学院,广东广州510006 [2]华中科技大学软件学院,湖北武汉430074

出　　处：《软件学报》2012年第12期3221-3232,共12页Journal of Software

基　　金：国家自然科学基金(60973085);国家高技术研究发展计划(863)(2006AA04Z211);广东省自然科学基金(S2011040005815);广东高校优秀青年创新人才培养计划(LYM11015);教育部博士点基金(20120172120036);中央高校基本科研业务费专项资金(2011ZM0074);国家级大学生创新训练计划(111056154)

摘　　要：借助于二值图像的可重叠矩形区域编码的思想,通过使用可重叠矩形非对称逆布局的模式表示模型(RNAM)和扩展的Gouraud阴影法,给出了可重叠同类块逆布局的4个准则,提出了一种基于可重叠RNAM的灰度图像表示算法,简称为ORNAMC表示算法.在ORNAMC表示算法中,通过使用3个用于标识顶点类型的水平矩阵H、垂直矩阵V和单点矩阵I代替混合矩阵R,解决了灰度图像的可重叠RNAM表示中矩阵R的不可解码性问题;同时,通过将顶点类型及码字进行重新定义,提出了一种对矩阵H,V和I中所有非零元素坐标进行编码的坐标数据压缩算法.以图像处理领域里惯用的标准灰度图像等作为典型测试对象,实验结果表明,与已提出的非重叠RNAMC和流行的STC,SDCT等灰度图像表示方法相比,在保持图像质量的前提下,ORNAMC表示方法具有更高的压缩比和更少的块数,因而是灰度图像表示的一种更好的方法.The idea of an overlapping rectangular region coding of binary images inspired the overlapping rectangular non-symmetry, the anti-packing pattern representation model （RNAM）, and the extended Gouraud shading approach. A novel lossy gray image representation algorithm based on the overlapping RNAM, which is called ORNAMC representation algorithm, is proposed. Also, the four principles for anti-packing the overlapping homogenous blocks are presented in this paper. In the proposed ORNAMC representation algorithm, the wrong decoding problem of the matrix R for the overlapping RNAM representation of gray images is solved separately by using the horizontal, vertical, and isolated matrices, i.e., H, V and L These are used to identify the vertex types instead of using a single hybrid matrix, i.e., R. In addition, by redefining the codeword set for the three vertices symbols, this paper proposed a new coordinate data compression algorithm for coding the coordinates of all non-zone elements in the three matrices H, V and L By taking some idiomatic standard gray images in the field of image processing as typical test objects, and by comparing the proposed ORNAMC representation algorithm with the latest non-overlapping RNAMC, the experimental results show that the former has a higher compression ratio and a fewer number of blocks and yet, maintains image quality. Therefore, a better method is to represent the gray image.

关 键 词：图像表示 矩形非对称逆布局的模式表示模型(RNAM) 可重叠 灰度图像 扩展的Gouraud阴影法 SDCT STC 坐标数据压缩 同类块 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]