Acta Photonica Sinica, Volume. 52, Issue 4, 0430002(2023)

Hyperspectral Image Denoising Based on Fast Tri-factorization and Group Sparsity Regularized

Xiaoyu GAO1, Jingyuan BAI1, Yangzhi HUANG2, and Jifeng NING1、*
Author Affiliations
  • 1College of Information Engineering, Northwest Agriculture & Forestry University, Yangling712100, China
  • 2College of Science, Northwest Agriculture & Forestry University, Yangling712100, China
  • show less
    References(25)

    [1] LIU C, TAO R, LI W et al. Joint classification of hyperspectral and multispectral images for mapping coastal wetlands[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 982-996(2020).

    [2] WANG R, NIE F, WANG Z et al. Multiple features and isolation forest-based fast anomaly detector for hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 58, 6664-6676(2020).

    [3] ZHONG Y, RU C, WANG S et al. An online, non-destructive method for simultaneously detecting chemical, biological, and physical properties of herbal injections using hyperspectral imaging with artificial intelligence[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 264, 120250(2022).

    [4] HONG D, WU X, GHAMISI P et al. Invariant attribute profiles: a spatial-frequency joint feature extractor for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 58, 3791-3808(2020).

    [5] FU H, ZHANG A, SUN G et al. A novel band selection and spatial noise reduction method for hyperspectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-13(2022).

    [6] LIU J, YUAN S, ZHU X et al. Nonnegative matrix factorization with entropy regularization for hyperspectral unmixing[J]. International Journal of Remote Sensing, 42, 6359-6390(2021).

    [7] WANG Q, WU Z, JIN J et al. Low rank constraint and spatial spectral total variation for hyperspectral image mixed denoising[J]. Signal Processing, 142, 11-26(2018).

    [8] ZENG H, XIE X, CUI H et al. Hyperspectral image restoration via global L 1-2 spatial-spectral total variation regularized local low-rank tensor recovery[J]. IEEE Transactions on Geoscience and Remote Sensing, 59, 3309-3325(2020).

    [9] CANDÈS E J, LI X, MA Y et al. Robust principal component analysis?[J]. Journal of the ACM, 58, 1-37(2011).

    [10] HE W, ZHANG H, SHEN H et al. Hyperspectral image denoising using local low-rank matrix recovery and global spatial-spectral total variation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 713-729(2018).

    [11] HU Y, ZHANG D, YE J et al. Fast and accurate matrix completion via truncated nuclear norm regularization[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 2117-2130(2012).

    [12] PENG C, KANG Z, LI H et al. Subspace clustering using log-determinant rank approximation[C], 925-934(2015).

    [13] HUANG X, DU B, TAO D et al. Spatial-spectral weighted nuclear norm minimization for hyperspectral image denoising[J]. Neurocomputing, 399, 271-284(2020).

    [14] ZENG H, XIE X, NING J. Hyperspectral image denoising via global spatial-spectral total variation regularized nonconvex local low-rank tensor approximation[J]. Signal Processing, 178, 107805(2021).

    [15] LIU Y, JIAO L C, SHANG F. A fast tri-factorization method for low-rank matrix recovery and completion[J]. Pattern Recognition, 46, 163-173(2013).

    [16] LIU Q, DAVOINE F, YANG J et al. A fast and accurate matrix completion method based on QR decomposition and L2,1-norm minimization[J]. IEEE Transactions on Neural Networks and Learning Systems, 30, 803-817(2018).

    [17] CHEN Y, HUANG T Z, HE W et al. Hyperspectral image denoising using factor group sparsity-regularized nonconvex low-rank approximation[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-16(2021).

    [18] CHEN Y, HE W, ZHAO X L et al. Exploring nonlocal group sparsity under transform learning for hyperspectral image denoising[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-18(2022).

    [19] CHEN Y, HUANG T Z, DENG L J et al. Group sparsity based regularization model for remote sensing image stripe noise removal[J]. Neurocomputing, 267, 95-106(2017).

    [20] CHEN Y, HE W, YOKOYA N et al. Hyperspectral image restoration using weighted group sparsity-regularized low-rank tensor decomposition[J]. IEEE Transactions on Cybernetics, 50, 3556-3570(2020).

    [21] ZHANG Hongyan, HE Wei, ZHANG Liangpei et al. Hyperspectral image restoration using low-rank matrix recovery[J]. IEEE Transactions on Geoscience and Remote Sensing, 52, 4729-4743(2014).

    [22] BOYD S, PARIKH N, CHU E et al. Distributed optimization and statistical learning via the alternating direction method of multipliers[J]. Foundations and Trends® in Machine Learning, 3, 1-122(2011).

    [23] LIU G, LIN Z, YAN S et al. Robust recovery of subspace structures by low-rank representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 171-184(2012).

    [24] WANG Y, PENG J, ZHAO Q et al. Hyperspectral image restoration via total variation regularized low-rank tensor decomposition[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 1227-1243(2018).

    [25] ZHANG L, ZHANG L, MOU X et al. FSIM: a feature similarity index for image quality assessment[J]. IEEE Transactions on Image Processing, 20, 2378-2386(2011).

    Tools

    Get Citation

    Copy Citation Text

    Xiaoyu GAO, Jingyuan BAI, Yangzhi HUANG, Jifeng NING. Hyperspectral Image Denoising Based on Fast Tri-factorization and Group Sparsity Regularized[J]. Acta Photonica Sinica, 2023, 52(4): 0430002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Oct. 9, 2022

    Accepted: Jan. 3, 2023

    Published Online: Jun. 21, 2023

    The Author Email: Jifeng NING (njf@nwafu.edu.cn)

    DOI:10.3788/gzxb20235204.0430002

    Topics