本文提出并分析了一个栅格—四叉树结构间的变换算法。
This paper advances and analyses an algorithm converting Raster to Quadtree.
实验表明，把四叉树结构引入图像分割，收到了较好的效果。
The experiment shows that it can receive satisfactory results using Quadtree techniques in image segmentation.
与常规四叉树结构比较，该方法具有压缩率高、表达直接等优点。
Compared with ordinary quadtree, it has some advantages including a high rate of compression and a direct representation.
四叉树数据结构的特性与其邻域寻找算法，并将多分辨率影像数据按照四叉树结构进行分块处理；
The unique properties of quad tree data structure and divided pyramid image into partitions by using quad tree methods;
为了解决单张高分辨率纹理映射的问题，我们利用纹理在绘制中的连贯性，将纹理数据组织为四叉树结构。
Exploiting the frame coherence, we construct the texture data as quadtree, and integrated with geometry quadtree, which handle the problem of large texture in real-time.
每个结点表示一个DEM数据分块，根据如此剖分，由这棵四叉树结构就得到全球范围不同分辨率的DEM数据存储结构。
Each node represents one DEM data block. According this separation, by quad-tree data structure can get global different resolution DEM data storage architecture.
每个结点表示一个DEM数据分块，根据如此剖分，由这棵四叉树结构就得到全球范围不同分辨率的DEM数据存储结构。
Each node represents one DEM data block. According this separation, by quad-tree data structure can get global different resolution DEM data storage architecture.
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