检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:马伯宁[1] 冷志光[1] 汤晓安[1] 匡纲要[1]
机构地区:[1]国防科学技术大学电子科学与工程学院,长沙410073
出 处:《中国图象图形学报》2012年第2期197-202,共6页Journal of Image and Graphics
摘 要:栅格数据金字塔是空间信息系统中的一类基本组织结构,基于小波的金字塔构建方法需要考虑数据分块导致的边界问题,现有算法或者未考虑边界问题,或者在消除边界缝隙问题时需增加大量的计算。针对分块数据小波变换的边界问题,提出分块数据的小波系数拼接算法,该算法对相邻子块边界系数进行叠加,使拼接后的小波系数等效于直接对大数据进行小波变换。在此基础上,提出无缝栅格数据小波金字塔构建方法:首先对大块数据进行分块多级小波变换,然后利用小波系数拼接算法完成对各块系数的无缝拼接。该金字塔结构消除了边界系数,实现了各子带小波系数的无缝组织。实验结果表明,拼接算法可大幅减少高层金字塔的数据量,且易于实现。A raster data pyramid is a basic data structure in spatial information systems. The boundary issue caused by blocking must be considered in a wavelet-based pyramid construction method. This issue is not mentioned in most existing algorithms or a large amount of calculations is needed to eliminate the border gap in those other methods. This paper presents a wavelet coefficient stitching algorithm for data blocks, which addresses the block boundaries in the wavelet transformation. The key point of our stitching algorithm is that one block coefficients is patched by its adjoining blocks boundary coefficients. The stitching result is equivalent to proceeding wavelet transformation on the whole data. A pyramid construction method is proposed that is named seamless wavelet pyramid construction method (SWPCM). In the SWPCM, the whole data is divided into a large number of blocks and a wavelet transformation is performed on each block. Then, the stitching algorithm is executed on the blocks' wavelet coefficients. The boundary coefficients are eliminated and data seamless organization is achieved with SWPCM. The experiments show that the stitching algorithm can significantly reduce the sizes of high level coefficients and that the proposed method is easy to implement.
关 键 词:影像金字塔 数据无缝组织 小波变换 小波系数拼接
分 类 号:TP311[自动化与计算机技术—计算机软件与理论]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.200