形态学对比度算子簇理论完善及其图像分析方法研究

This project is the further study of the preliminary achievements of the top-hat transform based morphological contrast operator in the National Natural Science Foundation (Youth Science Foundation), and is also the active research area in morphological image processing. Based on the analysis of the common properties of the toggle and top-hat transform based morphological contrast operators, the theoretical foundation of the family of morphological contrast operators and their multi-scale extension would be proposed. Thus, the effective image analysis tool based on the theoretical foundation of the family of morphological contrast operators could be constructed. This would reveal the theoretical foundation and effective ways of morphological contrast operator for wide applications of image processing and analysis. Firstly, the properties of toggle and top-hat transform based morphological contrast operators will be analyzed. Secondly, the construction of the family of morphological contrast operators will be discussed. Thirdly, the theory of constructing multi-scale space based on morphological contrast operator will be deeply studied. Fourthly, the image analysis method based on the theory of morphological contrast operator will be constructed and analyzed. Finally, the research on the applications of image enhancement and image quality measurement using morphological contrast operator will be also performed. The achievements of this project would form the foundation of the family of morphological contrast operator, and extend the effect and area of the applications of morphological contrast operator. These will provide new strategies or ways for the further improvement of morphological theory and the development of image processing technologies.

本项目是青年科学基金项目中基于Top-hat变换的对比度算子研究内容所取得的研究成果的深入拓展和形态学图像处理的重要研究热点。在分析Toggle及基于Top-hat变换的对比度算子共同特点的基础上，通过建立形态学对比度算子簇及其多尺度扩展理论，构造基于形态学对比度算子簇理论的有效图像分析工具，全面揭示形态学对比度算子进行有效而广泛图像处理与分析的理论基础和有效途径。研究内容包括：Toggle及基于Top-hat变换的对比度算子特性分析；形态学对比度算子簇的构建；基于对比度算子簇的多尺度空间构造基本理论研究；基于对比度算子簇理论的图像分析方法研究；对比度算子簇理论在图像增强与图像质量评价中的应用研究。研究成果将形成并奠定形态学对比度算子簇的理论基础，扩展形态学对比度算子的应用效果与范围，为数学形态学理论的进一步完善和图像处理技术的发展与应用提供新思路和新方法。

形态学理论完善和新运算构造是形态学理论与图像分析的研究前沿。任何一种新形态学运算的提出都对形态学图像分析理论有重要推动。本项目针对形态学对比度算子簇基本理论完善及其应用扩展问题开展深入研究，在完善形态学基本理论的基础上为图像分析实际应用提供了新的有效工具。主要研究内容和取得的成果如下：深入分析基于Toggle和Top-hat变换的对比度算子特性，有效扩展两类对比度算子的应用范围，为开展形态学对比度算子簇相关研究奠定基础；构建较为完善的形态学对比度算子簇理论，明确提出形态学对比度算子簇概念；构造基于形态学对比度算子簇的多尺度空间理论，扩展形态学多尺度理论，提出有效的基于形态学对比度算子簇的图像分析框架；提出基于形态学对比度算子簇理论的图像增强、融合等应用的有效算法。研究成果完善了形态学基本理论，为图像分析应用提供了一类有效的形态学新工具，为形态学理论发展和图像分析应用作出了积极贡献。发表包括领域内权威期刊在内的国际SCI刊物论文27篇，申请发明专利7项，授权发明专利2项。项目执行期间，晋升教授1人，毕业硕士研究生3人、博士研究生2人，博士后出站2人，获国家技术发明二等奖1人次。