Optics and Precision Engineering, Volume. 30, Issue 12, 1487(2022)

Lightweight Mars remote sensing image super-resolution reconstruction network

Mingkun GENG1,2, Fanlu WU1,3, and Dong WANG1、*
Author Affiliations
  • 1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun30033, China
  • 2University of Chinese Academy of Sciences, Beijing100049, China
  • 3Key Laboratory of Lunar and Deep Space Exploration, Chinese Academy of Sciences, Beijing100101, China
  • show less
    References(25)

    [1] J L HARRIS. Diffraction and resolving power. Journal of the Optical Society of America, 54, 931(1964).

    [2] R TSAI, T S HUANG. Multiple frame image restoration and registration. Advances in Computer Vision and Image Processing, 1, 317-319(1984).

    [3] K I KIM, Y KWON. Single-image super-resolution using sparse regression and natural image prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32, 1127-1133(2010).

    [4] M IRANI, S PELEG. Improving resolution by image registration. CVGIP: Graphical Models and Image Processing, 53, 231-239(1991).

    [5] [5] 5彭真明, 景亮, 何艳敏, 等. 基于多尺度稀疏字典的多聚焦图像超分辨融合[J]. 光学 精密工程, 2014, 22(1): 169-176. doi: 10.3788/OPE.20142201.0169PENGZ M, JINGL, HEY M, et al. Superresolution fusion of multi-focus image based on multiscale sparse dictionary[J]. Optics and Precision Engineering, 2014, 22(1): 169-176.(in Chinese). doi: 10.3788/OPE.20142201.0169

    [6] K B ZHANG, X B GAO, D C TAO et al. Single image super-resolution with non-local means and steering kernel regression. IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society, 21, 4544-4556(2012).

    [7] H HE, W C SIU. Single image super-resolution using Gaussian process regression, 449-456(2011).

    [8] [8] 8李勇, 王珂, 张立保, 等. 多断层融合的肺CT肿瘤靶区超分辨率重建[J]. 光学 精密工程, 2010, 18(5): 1212-1218. doi: 10.3788/OPE.20101805.1212LIY, WANGK, ZHANGL B, et al. Super-resolution reconstruction of pulmonary nodules based on CT multi-section fusion[J]. Optics and Precision Engineering, 2010, 18(5): 1212-1218.(in Chinese). doi: 10.3788/OPE.20101805.1212

    [9] [9] 9吴炜, 杨晓敏, 陈默, 等. 一种新颖的人脸图像超分辨率技术[J]. 光学 精密工程, 2008, 16(5): 815-821. doi: 10.3321/j.issn:1004-924X.2008.05.010WUW, YANGX M, CHENM, et al. Novel method of face hallucination[J]. Optics and Precision Engineering, 2008, 16(5): 815-821.(in Chinese). doi: 10.3321/j.issn:1004-924X.2008.05.010

    [10] [10] 10符冉迪, 周颖, 颜文, 等. 基于TV-L1分解的红外云图超分辨率算法[J]. 光学 精密工程, 2016, 24(4): 937-944. doi: 10.3788/OPE.20162404.0937FUR D, ZHOUY, YANW, et al. Infrared nephogram super-resolution algorithm based on TV-L1 decomposition[J]. Optics and Precision Engineering, 2016, 24(4): 937-944.(in Chinese). doi: 10.3788/OPE.20162404.0937

    [11] [11] 11朱福珍, 刘越, 黄鑫, 等. 改进的稀疏表示遥感图像超分辨重建[J]. 光学 精密工程, 2019, 27(3): 718-725. doi: 10.13482/j.issn1001-7011.2019.05.004ZHUF Z, LIUY, HUANGX, et al. Remote sensing image super-resolution based on improved sparse representation[J]. Optics and Precision Engineering, 2019, 27(3): 718-725.(in Chinese). doi: 10.13482/j.issn1001-7011.2019.05.004

    [12] S C LIU, H ZHAO, Q DU et al. Novel cross-resolution feature-level fusion for joint classification of multispectral and panchromatic remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-14(2022).

    [13] Y J ZHENG, S C LIU, Q DU et al. A novel multitemporal deep fusion network (MDFN) for short-term multitemporal HR images classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10691-10704(14).

    [14] C DONG, C C LOY, K M HE et al. Image super-resolution using deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 295-307(2016).

    [15] J KIM, J K LEE, K M LEE. Deeply-recursive convolutional network for image super-resolution, 1637-1645(2016).

    [16] W S LAI, J B HUANG, N AHUJA et al. Deep Laplacian pyramid networks for fast and accurate super-resolution, 5835-5843(2017).

    [17] E H ADELSON, C H ANDERSON, J R BERGEN et al. Pyramid methods in image processing. RCA engineer, 29, 33-41(1984).

    [18] P J BURT, E H ADELSON. The Laplacian Pyramid as a Compact Image Code. Readings in Computer Vision, 671-679(1987).

    [19] S PARIS, S W HASINOFF, J KAUTZ. Local Laplacian filters: edge-aware image processing with a Laplacian pyramid. Communications of the ACM, 58, 81-91(2015).

    [20] G GHIASI, C C FOWLKES. Laplacian pyramid reconstruction and refinement for semantic segmentation, 2016, 519-534(2016).

    [21] W C WANG, F L CHANG. A multi-focus image fusion method based on Laplacian pyramid. Journal of Computers, 6, 2559-2566(2011).

    [22] E L DENTON, S CHINTALA, R FERGUS. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. Advances in Neural Information Processing System, 28(2015).

    [23] W S LAI, J B HUANG, N AHUJA et al. Fast and accurate image super-resolution with deep Laplacian pyramid networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41, 2599-2613(2019).

    [24] A S MCEWEN, E M ELIASON, J W BERGSTROM et al. Mars reconnaissance orbiter's high resolution imaging science experiment (HiRISE). Journal of Geophysical Research: Planets, 112, E05-02(2007).

    [25] K M HE, X Y ZHANG, S Q REN et al. Delving deep into rectifiers: surpassing human-level performance on ImageNet classification, 1026-1034(2015).

    CLP Journals

    [1] Yuhong LIU, Heng YANG. Iterative reconstruction of compressive sensing combining image hierarchical-feature[J]. Optics and Precision Engineering, 2024, 32(14): 2311

    Tools

    Get Citation

    Copy Citation Text

    Mingkun GENG, Fanlu WU, Dong WANG. Lightweight Mars remote sensing image super-resolution reconstruction network[J]. Optics and Precision Engineering, 2022, 30(12): 1487

    Download Citation

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

    Category: Information Sciences

    Received: Dec. 23, 2021

    Accepted: --

    Published Online: Jul. 5, 2022

    The Author Email: WANG Dong (wangd@ciomp.ac.cn)

    DOI:10.37188/OPE.20223012.1487

    Topics