J. Vass, Jia Yao, A. Joshi, K. Palaniappan, X. Zhuang
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引用次数: 15
摘要
开发了一个高效的图像数据库系统。该系统的主要特点包括压缩域索引、利用可扩展特征进行搜索和渐进图像传输。在搜索细化阶段和查询结果的显示中都涉及到用户交互。最重要的查询类型包括按颜色布局查询和按小波系数聚类信息查询。索引和搜索算法与底层图像压缩算法紧密耦合,将图像存储在数据库中,降低了数据库管理系统的复杂性和存储需求。在本研究中,我们利用我们之前开发的(b - b)。Chai et al., 1997,1998)的高性能小波图像编码算法,称为“意义关联连通分量分析”,与其他顶级小波图像编码算法和JPEG标准相比,该算法不仅具有非常高的压缩性能,而且具有固有的可扩展性和累进传输特性。计算机实验证明了所开发系统的有效性。
An efficient image database system is developed. The most important features of the proposed system include compressed domain indexing, searching by using scalable features, and progressive image transmission. User interaction is involved both at the search refinement stage and in the display of the query results. The most important query types include query by color layout and query by wavelet-coefficient clustering information. The indexing and searching algorithms are tightly coupled with the underlying image compression algorithm by which means the images are stored in the database, reducing both the complexity and the storage requirements of the database management system. In this research, we utilize our previously developed (B.-B. Chai et al., 1997, 1998) high-performance wavelet image coding algorithm, termed "significance-linked connected component analysis", which not only renders a very high compression performance when compared to other top-ranked wavelet image coding algorithms and the JPEG standard, but also inherently supports scalable features and progressive transmission. Computer experiments demonstrate the efficiency of the developed system.