Complex nonseparable oversampled lapped transform for sparse representation of millimeter wave radar image

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

Abstract

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.
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
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。
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