兰州大学机构库 >数学与统计学院
DTCC变换及其在图像挖掘中的应用
Alternative TitleDTCC and Its Applications in Image Mining
刘莉
Thesis Advisor李廉
2012-05-27
Degree Grantor兰州大学
Place of Conferral兰州
Degree Name博士
Keyword图像挖掘 DTCC 平移不变性 方向性分辨率 多分辨率分析 HMT 关联规则 纹理检索 分类算法 图像分类
Abstract论文主要研究方向性多分辨率分析方法DTCC 及其在图像处理和图像数据挖掘中的应用。 1、基于DTCWT的思想,论文构造了一种对偶树结构的LP变换,结合DFBs方向性分解的能力,实现了一种近似平移不变的方向性多分辨率方法,称为对偶树复Contourlet变换DTCC。DTCC变换具有近似的平移不变性,方向性分辨率高,且拥有相信息,最高具有8/3的冗余度。 2、论文完成了基于DTCC的图像除噪和纹理检索实验,实验结果显示DTCC具有较理想的除噪和检索分类功能,表明DTCC是一种良好的方向性多分辨率分析方法。 3、论文建立了DTCC的HMT模型,并将其应用于图像除噪和纹理检索中。实验结果表明,基于DTCC 的HMT模型在图像除噪和纹理检索等方面均优于Contourlet HMT模型。 4、论文以DTCC变换为基础,在方向子带中,构建了描述图像微结构的事务,挖掘得到图像数据中的关联规则,以它们的统计参数作为图像特征,应用于图像分类中。实验表明基于DTCC域关联规则的挖掘算法能发现图像微结构间隐藏的共生模式特征,具有良好的分类效果。 5、根据掌纹图像的特点,提出一种掌纹图像挖掘算法,应用于掌纹分类中。
Other AbstractThis thesis mainly studies the directional multiresolution transform DTCC and its application in image processing and image data mining. First of all, we construct a dual tree LP transform based on the motivation of DTCWT for the purpose of improving the shift invariance of LP, and combine the DFBs which ensures the higher directional selectivity, then implement a near shift invariance and higher direction selectivity transform which is named as dual tree complex Contourlet, DTCC. Secondly, we apply DTCC to image denoising and texture retrieval. Thirdly, we built the HMT model based on DTCC in order to reveal the dependence existing among the DTCC coefficients. Fourthly, we propose an image classification method based on association rule under DTCC. Finally, we introduce a mining algorithm on palmprint image according to the characteristics of palmprint images and use it in palmprint image classification.
URL查看原文
Language中文
Document Type学位论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/225716
Collection数学与统计学院
Recommended Citation
GB/T 7714
刘莉. DTCC变换及其在图像挖掘中的应用[D]. 兰州. 兰州大学,2012.
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