复不可分过采样重叠变换在毫米波雷达图像稀疏表示中的应用

S. Nagayama, Shogo M. Ramats, Hiroyoshi Yamada, Yuuichi S. Giyama
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引用次数: 3

摘要

这项工作推广了现有的不可分离过采样重叠变换(nsolt)框架,以有效地表示复值图像。原始的nsolt是基于晶格结构的冗余变换,满足线性相位、紧支持和实值性质。该点阵结构能够构成具有合理冗余的Parseval紧框架,并生成具有定向原子图像的字典。在这项研究中,提出了一种广义的nsolt结构来覆盖复值原子图像。这种新的变换被称为复NSOLT (CNSOLT)。利用迭代硬阈值(IHT)算法对毫米波雷达图像进行稀疏逼近,验证了该结构的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Complex nonseparable oversampled lapped transform for sparse representation of millimeter wave radar image
This work generalizes an existing framework of nonseparable oversampled lapped transforms (NSOLTs) to effectively represent complex-valued images. The original NSOLTs are lattice-structure-based redundant transforms, which satisfy the linear-phase, compact-supported and real-valued property. The lattice structure is able to constitute a Parseval tight frame with rational redundancy and to generate a dictionary with directional atomic images. In this study, a generalized structure of NSOLTs is proposed to cover complex-valued atomic images. The novel transform is referred to as a complex NSOLT (CNSOLT). The effectiveness of the structure is verified by evaluating the sparse approximation performance using the iterative hard thresholding (IHT) algorithm for a millimeter wave radar image.
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