Optics and Precision Engineering, Volume. 32, Issue 20, 3047(2024)
End-to-end deblurring model for microscopic vision
[1] SAGE D, DONATI L, SOULEZ F et al. DeconvolutionLab2: an open-source software for deconvolution microscopy[J]. Methods, 115, 28-41(2017).
[2] LIN F, JIN C H. An improved Wiener deconvolution filter for high-resolution electron microscopy images[J]. Micron, 50, 1-6(2013).
[3] ZHANG M N, FANG Y Y, NI G X et al. Pixel screening based intermediate correction for blind deblurring[C], 1-9(2022).
[4] XU Z H, CHEN H S, LI Z H. Fast blind deconvolution using a deeper sparse patch-wise maximum gradient prior[J]. Signal Processing: Image Communication, 90, 116050(2021).
[5] LEVIN A, WEISS Y, DURAND F et al. Understanding and evaluating blind deconvolution algorithms[C], 1964-1971(2009).
[6] FERGUS R, SINGH B, HERTZMANN A et al. Removing camera shake from a single photograph[J]. ACM Transactions on Graphics, 25, 787-794(2006).
[7] LEDIG C, THEIS L, HUSZÁR F et al. Photo-realistic single image super-resolution using a generative adversarial network[C], 105-114(2017).
[8] YANG F Z, YANG H, FU J L et al. Learning texture transformer network for image super-resolution[C], 5790-5799(2020).
[9] LU Z S, LI J C, LIU H et al. Transformer for single image super-resolution[C], 456-465(2022).
[10] LIU Y, CHEN X, PENG H et al. Multi-focus image fusion with a deep convolutional neural network[J]. Information Fusion, 36, 191-207(2017).
[11] WU P, JIANG L M, HUA Z et al. Multi-focus image fusion: transformer and shallow feature attention matters[J]. Displays, 76, 102353(2023).
[12] WANG C, ZHAO Z Y, REN Q Q et al. A novel multi-focus image fusion by combining simplified very deep convolutional networks and patch-based sequential reconstruction strategy[J]. Applied Soft Computing, 91, 106253(2020).
[13] 赵宇轩. 单图超分辨光片显微成像技术及其在活细胞中的应用研究[D](2022).
ZHAO Y X.
[14] 朱威铭. 基于生成对抗学习的煤岩显微图像超分辨率重建[D](2023).
ZHU W M.
[15] 陈浩. 基于视觉特征的显微图像预处理研究[D](2020).
CHEN H. Microscopic Image Preprocessing Based on Visual Features[D](2020).
[16] 徐征, 陈聿夫, 孙谦. 机器视觉精密测量中的显微光学聚焦[J]. 光学 精密工程, 24, 2095-2100(2016).
XU Z, CHEN Y F, SUN Q et al. Auto-focusing in optical microscopy for machine-vision-based precise measurement[J]. Opt. Precision Eng., 24, 2095-2100(2016).
[17] ZHOU L P, SUN Z J, ZHANG Q. Auto-focusing and control of micro-vision system[J]. Opt. Precision Eng., 21, 807-812(2013).
周丽平, 孙志峻, 张泉. 显微视觉系统的自动聚焦及控制[J]. 光学 精密工程, 21, 807-812(2013).
[18] MAIER A. Efficient focus assessment for a computer vision-based Vickers hardness measurement system[J]. Journal of Electronic Imaging, 21(2012).
[19] SI J, XIAO X, LI J et al. Super-resolution reconstruction algorithm with multi-frame defocused images based on generative adversarial network[J]. Computer Engineering, 47, 266-273(2021).
斯捷, 肖雄, 李泾. 基于生成对抗网络的多幅离焦图像超分辨率重建算法[J]. 计算机工程, 47, 266-273(2021).
[20] HE K M, ZHANG X Y, REN S Q et al. Deep residual learning for image recognition[C], 770-778(2016).
[22] KIM J, LEE J K, LEE K M. Accurate image super-resolution using very deep convolutional networks[C], 1646-1654(2016).
[23] DONG C, LOY C C, HE K M et al. Image super-resolution using deep convolutional networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 295-307(2016).
Get Citation
Copy Citation Text
Zheng XU, Jiaheng HE, Yanqi WANG, Xiaodong WANG, Tongqun REN. End-to-end deblurring model for microscopic vision[J]. Optics and Precision Engineering, 2024, 32(20): 3047
Category:
Received: Mar. 25, 2024
Accepted: --
Published Online: Jan. 10, 2025
The Author Email: Xiaodong WANG (xdwang@dlut.edu.cn)