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字典学习模型、算法及其应用研究进展

DOI: 10.16383/j.aas.2015.c140252, PP. 240-260

Keywords: 字典学习,稀疏表示,综合模型,解析模型

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Abstract:

?稀疏表示模型常利用训练样本学习过完备字典,旨在获得信号的冗余稀疏表示.设计简单、高效、通用性强的字典学习算法是目前的主要研究方向之一,也是信息领域的研究热点.基于综合稀疏模型的字典学习方法已经广泛应用于图像分类、图像去噪、图像超分辨率和压缩成像等领域.近些年来,解析稀疏模型、盲字典模型和信息复杂度模型等新模型的出现丰富了字典学习理论,使得更广泛类型的信号能够被"简单性"描述.本文详细介绍了综合字典、解析字典、盲字典和基于信息复杂度字典学习的基本模型及其算法,阐述了字典学习的典型应用,指出了字典学习的进一步研究方向.

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