为了提高图像数据库的检索效率，必须提高高维索引的效率。
The enhancement of high-dimensional indexing technique is necessary to improve the performance of image database retrieval.
最后指出在空间数据库中的高维索引的研究是目前前沿研究的热点。
Finally, it is pointed out that the high dimensional index is a hot research field in spatial databases.
高维索引是一门比较新颖、比较有深度的学科，目前国内对这一方向的研究还比较少。
High-dimensional index is novelty and foreground aspect, The study of this field is weakly.
有效的高维索引机制是基于内容的图像检索的关键技术，具有重要的理论意义和应用价值。
Efficient indexing schemes for high-dimensional data are important for Content-Based Image Retrieval, with theoretical and applicable value as result.
为了提高高维数据相似查询的效率，提出一种基于双重距离尺度(DDM)的新型高维索引结构。
To speed up high-dimensional similarity search efficiency, a novel high-dimensional indexing structure based on dual distance metric (DDM) was proposed.
在基于高维索引技术的相似性查询处理中，通常通过过滤那些不包含任何查询结果的非活动子空间来不断缩减搜索空间。
In the similarity query processing based on high dimensional indexing, the searching space is usually narrowed down by pruning the inactive subspaces which do not contain any query results.
在基于高维索引技术的相似性查询处理中，通常通过过滤那些不包含任何查询结果的非活动子空间来不断缩减搜索空间。
In the similarity query processing based on high dimensional indexing, the searching space is usually narrowed down by pruning the inactive subspaces which do not contain any query results.
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