D2Net: Deep Denoising Network in Frequency Domain for Hyperspectral Image

被引：5

作者：

Pan, Erting ^{[1
]}

Ma, Yong ^{[1
]}

Mei, Xiaoguang ^{[1
]}

Huang, Jun ^{[1
]}

Fan, Fan ^{[1
]}

Ma, Jiayi ^{[1
]}

机构：

[1] Wuhan Univ, Elect Informat Sch, Wuhan 430072, Peoples R China

来源：

IEEE-CAA JOURNAL OF AUTOMATICA SINICA | 2023年 / 10卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Convolution; Discrete wavelet transforms; Image reconstruction; Kernel; Noise measurement; Noise reduction; Representation learning;

D O I：

10.1109/JAS.2022.106019

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to various unstable factors in the complex imaging chain, HSIs are always contaminated by noises, which will severely degrade the visual qualtiy and affect their further analysis and subsequent interpretations [1], [2]. Therefore, removing HSI noise is of utmost significance for HSI exploitation. IEEE

引用

页码：813 / 815

页数：3

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