Study on a high-level processing for large size image using a effective geometrical graphic data structure

本文提出并研究了一种新的基于软件的图象处理技术，它能实现高效率和智能化，特别适用于大尺寸（或大容量）图象数据，如各种类型的图形和彩色图象.在项目的第一阶段，提出了一种适用于二维或三维图形基元（线、面、体等）的高效通用数据结构，命名为BD树（图形），已被引入设计扩展的多维数据结构BD树，这是唯一的提出了这个研究小组在1983年。通过使用各种类型的真实的地图数据进行的大量计算机模拟，从存储器使用率和检索效率的角度，揭示了这种图形数据结构的有效性。大的图像数据，通常是8000 × 6000像素的游程编码方法，首先转换为 关于我们 用我们独特的方法将其转换成适当的图形基元，如轮廓矢量，然后将其动态插入到BD树（图形）中，为以后的处理做准备。所有所需的图像处理功能可以通过对表示原始图像的图形基元进行高效和智能的几何操作来执行。对原始图元的抽象层次由核心向量层次、更高的图元层次（如圆）、语义识别层次逐步提高。作为该框架的具体体现，本文用可移植的C语言实现了一个绘图处理器AI-MUDAMS，并提出了一种基于扩展三维BD树的颜色选择技术。通过对日本学术标准图像数据库SIDBA中1600万幅彩色图像进行16色256色的选择实验，验证了该方法的优越性。少

A new type of software-based image processing technique is proposed and investigated in this paper, which can realize very high efficiency and intelligence especially for large size (or large volume)image data such as various types of drawings and color images.In the first stage of the project, an efficient general purpose data structure suitable for 2 of 3 dimensional graphical primitives (lines, areas, volumes etc.),named the BD tree(graphic),has been introduced by devised extension of a multi-dimensional data structure BD tree which was proposed uniquely by this research group in 1983. Effectiveness of this graphical data structure has been revealed from the viewpoint of memory usage and retrieval efficiency through many computer simulations using a various types of real map data.In the next stage, a general framework for software-based large image processing has been proposed and evaluated. Large image data, typically 8000 by 6000 pixels coded by run-length method, are first conver … More ted into appropriate graphical primitives such as contour vectors by our unique method, which are then inserted bynamically to the BD tree(graphics) as preparation for hereafter processing. All the required image processing functions can be performed by a efficient and intelligent geometric operations on the graphical primitives representing the original image. Abstraction level for original graphical primitives are gradually enhanced through core vector level, higher graphical primitive level such as circle, and finally semantically recognized level. A drawing processor, the AI-MUDAMS is implemented using portable language C as a concrete embodiment of this general frame-work.In final, a new color selection technique using a similar framework using the extended threedimensional BD tree has been also proposed. Many experiments, including 16-color 256-dolor selection from 16 million color images in the Japanese Academic standard image database, SIDBA, reveals the superiority of the proposed method to other existing methods. Less