Removal of stripe noise with spatially adaptive unidirectional total variation-Reference-Cited by-同舟云学术

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Removal of stripe noise with spatially adaptive unidirectional total variation

Published:2014-06 Issue:12 Volume:125 Page:2756-2762
ISSN:0030-4026
Container-title:Optik
language:en
Short-container-title:Optik

Author:

Zhou Gang,Fang Houzhang,Yan Luxin,Zhang Tianxu,Hu Jing

Funder

Projection of the National Natural Science Foundation of China

National Natural Science Foundation of China

Innovation Research Fund Committee of HUST

Innovation Fund of CASC

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference9 articles.

1. Toward optimal destriping of modis data using a unidirectional variational model;Bouali;IEEE Trans. Geosci. Remote Sens.,2011

2. A MAP-based algorithm for destriping and inpainting of remotely sensed images;Shen;IEEE Trans. Geosci. Remote Sens.,2009

3. De-striping hyperspectral imagery using wavelet transform and adaptive frequency domain filtering;Pande-Chhetri;ISPRS J. Photogramm.,2011

4. Blind image deconvolution with spatially adaptive total variation regularization;Yan;Opt. Lett.,2012

5. Stripe and ring artifact removal with combined wavelet – Fourier filtering;Munch;Opt. Express,2009

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1. Stripe Noise Removal Algorithm for Infrared Remote Sensing Images Based on Adaptive Weighted Variable Order Model;Remote Sensing;2024-08-29

2. Adaptive stripe noise removal model based on spatial characteristics;MIPPR 2023: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications;2024-03-07

3. Stripe noise removal in conductive atomic force microscopy;Scientific Reports;2024-02-16

4. Deep Convolutional Neural Network (DCNN) for the Identification of Striping in Images of Blood Cells;Lecture Notes in Networks and Systems;2024

5. Destriping of Remote Sensing Images by an Optimized Variational Model;Sensors;2023-08-30

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