Singular spectrum analysis-based image sub-band decomposition filter banks

被引：0
|
作者：
Julia Evers
Florian Evers
Florian Goppelt
Ronald Schmidt-Vollus
机构：
[1] Nueremberg Campus of Technology,
[2] Technische Hochschule Nueremberg Georg Simon Ohm,undefined
[3] Independent researcher,undefined
来源：
EURASIP Journal on Advances in Signal Processing | / 2020卷
关键词：
Singular spectrum analysis; Singular value decomposition; Directional selectivity; Filter bank; Wavelet transform; Sub-band decomposition;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents a novel type of a filter bank for image decomposition that incorporates “singular spectrum analysis” (SSA). SSA is based on “singular value decomposition” (SVD).The presented filter banks provide good directional selectivity. Sub-band images highlight exposed directional features such as 0∘,90∘,+ 45∘, and − 45∘ of the input image. The proposed method can be seen as a tool to separate an image into layers or to present an image as a sum of its high-frequency directional components and a low-frequency approximation.
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