Rucco A, Sujit P, Aguiar AP, De Sousa JB, Pereira FL. Optimal rendezvous trajectory for unmanned aerial-ground vehicles. IEEE Trans Aerosp Electron Syst. 2017;54(2):834–47. https://doi.org/10.1109/TAES.2017.2767958.

Article  Google Scholar 

Kimura R, Yoshimura Y. The contribution of low contrast-preferring neurons to information representation in the primary visual cortex after learning. Sci Adv. 2021;7(48):9976. https://doi.org/10.1126/sciadv.abj9976.

Article  Google Scholar 

Wu S, Huang J, Feng Y, Sun B. Multiple reliable structured patches for object tracking. Cogn Comput. 2021;13(4):1593–602. https://doi.org/10.1007/s12559-020-09741-5.

Article  Google Scholar 

Hartley R, Kamgar-Parsi B, Narber C. Using roads for autonomous air vehicle guidance. IEEE Trans Intell Transp Syst. 2018;19(12):3840–9. https://doi.org/10.1109/TITS.2018.2799485.

Article  Google Scholar 

Yang W, Wang S, Fang Y, Wang Y, Liu J. From fidelity to perceptual quality: a semi-supervised approach for low-light image enhancement. In: 2020 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2020. p. 3063–3072. https://doi.org/10.1109/CVPR42600.2020.00313.

Ren W, Liu S, Ma L, Xu Q, Xu X, Cao X, Du J, Yang MH. Low-light image enhancement via a deep hybrid network. IEEE Trans Image Process. 2019;28(9):4364–75. https://doi.org/10.1109/TIP.2019.2910412.

Article  MathSciNet  MATH  Google Scholar 

Wang R, Zhang Q, Fu CW, Shen X, Jia J. Underexposed photo enhancement using deep illumination estimation. In: 2019 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2019. p. 6849–6857. https://doi.org/10.1109/CVPR.2019.00701.

Shen Z, Wang W, Lu X, Shen J, Ling H, Xu T, Shao L. Human-aware motion deblurring. In: 2019 IEEE International Conference on Computer Vision(ICCV); 2019. p. 5572–5581. https://doi.org/10.1109/ICCV.2019.00567.

Shen Z, Lai W-S, Xu T, Kautz J, Yang M-H. Deep semantic face deblurring. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2018. p. 8260–8269. https://doi.org/10.1109/CVPR.2018.00862.

Kupyn O, Budzan V, Mykhailych M, Mishkin D, Matas J. Deblurgan: blind motion deblurring using conditional adversarial network. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2018. p. 8183–8192. https://doi.org/10.1109/CVPR.2018.00854.

Chen S-J, Shen H-L. Multispectral image out-of-focus deblurring using interchannel correlation. IEEE Trans Image Process. 2015;24(11):4433–45. https://doi.org/10.1109/TIP.2015.2465162.

Article  MathSciNet  MATH  Google Scholar 

Iqbal M, Riaz MM, Ghafoor A, Ahmad A, Ali SS. Out of focus multi-spectral image de-blurring using texture extraction and modified Fourier transform. Multimed Tools Appl. 2021;80(8):12671–84. https://doi.org/10.1007/s11042-020-10232-w.

Article  Google Scholar 

Li X, Wu J, Liu Z, Zha H. Recurrent squeeze-and-excitation context aggregation net for single image deraining. In: 2018 European Conference on Computer Vision(ECCV); 2018. p. 254–269. https://doi.org/10.1007/978-3-030-01234-2_16.

He Z, Vishal MP. Densely connected pyramid dehazing network. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2018. p. 3194–3203. https://doi.org/10.1109/CVPR.2018.00337.

Ren W, Ma L, Zhang J, Pan J, Cao X, Liu W, Yang MH. Gated fusion network for single image dehazing. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2018. p. 3253–3261. https://doi.org/10.1109/CVPR.2018.00343.

Li H, Li G, Yan W, He G, Lin L. Synergy effect and its application in led-multispectral imaging for improving image quality. Opt Commun. 2019;438(1):6–12. https://doi.org/10.1016/j.optcom.2018.12.091.

Article  Google Scholar 

Xie Q, Zhao Q, Meng D, Xu Z. Kronecker-basis-representation based tensor sparsity and its applications to tensor recovery. IEEE Trans Pattern Anal Mach Intell. 2017;54(8):1888–902. https://doi.org/10.1109/TPAMI.2017.2734888.

Article  Google Scholar 

He W, Yao Q, Li C, Yokoya N, Zhao Q, Zhang H, Zhang L. Non-local meets global: an iterative paradigm for hyperspectral image restoration. IEEE Trans Pattern Anal Mach Intell. 2022;44(4):2089–107. https://doi.org/10.1109/TPAMI.2020.3027563.

Article  Google Scholar 

Chen Y, Guo Y, Wang Y, Wang D, Peng C, He G. Denoising of hyperspectral images using nonconvex low rank matrix approximation. IEEE Trans Geosci Remote Sens. 2017;55(9):5366–80. https://doi.org/10.1109/TGRS.2017.2706326.

Article  Google Scholar 

Sun H, Zheng X, Lu X, Wu S. Spectral-spatial attention network for hyperspectral image classification. IEEE Trans Geosci Remote Sens. 2019;58(5):3232–45. https://doi.org/10.1109/TGRS.2019.2951160.

Article  Google Scholar 

Chen W, Zheng X, Lu X. Semisupervised spectral degradation constrained network for spectral super-resolution. IEEE Geosci Remote Sens Lett. 2021;19(1):1–5. https://doi.org/10.1109/LGRS.2021.3079961.

Article  Google Scholar 

Sun H, Zheng X, Lu X. A supervised segmentation network for hyperspectral image classification. IEEE Trans Image Process. 2021;30(1):2810–25. https://doi.org/10.1109/TIP.2021.3055613.

Article  Google Scholar 

Malik M, Majumder S. Weather-predicting atmospheric modulation transfer function. In: 2013 3rd IEEE International Advance Computing Conference(IACC); 2013. p. 1613–1619. https://doi.org/10.1109/IAdCC.2013.6514469.

Saiga R, Takeuchi A, Uesugi K, Terada Y, Suzuki Y, Mizutani R. Method for estimating modulation transfer function from sample images. Micron. 2018;105:64–9. https://doi.org/10.1016/j.micron.2017.11.009.

Article  Google Scholar 

Ren W, Zhang J, Ma L, Pan J, Cao X, Zuo W, Liu W, Yang M-H. Deep non-blind deconvolution via generalized low-rank approximation. Adv Neural Inf Process Syst (NeurIPS). 2018;31(1):297–307.

Zhang M, Young GS, Tie Y, Gu X, Xu X. A new framework of designing iterative techniques for image deblurring. Pattern Recogn. 2022;124:108463. https://doi.org/10.1016/j.patcog.2021.108463.

Article  Google Scholar 

He K, Sun J, Tang X. Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell. 2010;33(12):2341–53. https://doi.org/10.1109/TPAMI.2010.168.

Article  Google Scholar 

Berman D, Avidan S, et al. Non-local image dehazing. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2016. p. 1647–1682. https://doi.org/10.1109/CVPR.2016.185.

Zhang Z, Zheng L, Piao Y, Tao S, Xu W, Gao T, Wu X. Blind remote sensing image deblurring using local binary pattern prior. Remote Sens. 2022;14(5):1276. https://doi.org/10.3390/rs14051276.

Article  Google Scholar 

Pan L, Hartley R, Liu M, Dai Y. Phase-only image based kernel estimation for single image blind deblurring. In: 2019 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2019. p. 6034–6043. https://doi.org/10.1109/CVPR.2019.00619.

Wang Z, Ren J, Zhang J, Luo P. Image deblurring aided by low-resolution events. Electronics. 2022;11(4):631. https://doi.org/10.3390/electronics11040631.

Article  Google Scholar 

Chen L, Fang F, Wang T, Zhang G. Blind image deblurring with local maximum gradient prior. In: 2019 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2019. p. 1742–1750. https://doi.org/10.1109/CVPR.2019.00184.

Shi Y, Wang N, Yang F, Zhang G, Li S, Liu X. Multispectral images deblurring via interchannel correlation relationship. In: 2021 4th International Conference on Information Communication and Signal Processing (ICICSP); 2021. p. 458–462. https://doi.org/10.1109/ICICSP54369.2021.9611913.

Pan J, Hu Z, Su Z, Lee H-Y, Yang M-H. Soft-segmentation guided object motion deblurring. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2016. p. 459–468. https://doi.org/10.1109/CVPR.2016.56.

Yan Y, Ren W, Guo Y, Rui W, Cao X. Image deblurring via extreme channels prior. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2017. p. 4003–4011. https://doi.org/10.1109/CVPR.2017.738.

Bai Y, Cheung G, Liu X, Gao W. Graph-based blind image deblurring from a single photograph. IEEE Trans Image Process. 2019;28(3):1404–18. https://doi.org/10.1109/TIP.2018.2874290.

Article  MathSciNet  Google Scholar 

Wen F, Ying R, Liu Y, Liu P, Truong TK. A simple local minimal intensity prior and an improved algorithm for blind image deblurring. IEEE Trans Circuits Syst Video Technol. 2021;31(8):2923–37. https://doi.org/10.1109/TCSVT.2020.3034137.

Article  Google Scholar 

Wei X-X, Zhang L, Huang H. High-quality blind defocus deblurring of multispectral images with optics and gradient prior. Opt Express. 2020;28(7):106883–10704.

Article  Google Scholar 

Guo X, Yang Y, Wang C, Ma J. Image dehazing via enhancement, restoration, and fusion: a survey. Inf Fusion. 2022;86:146–70. https://doi.org/10.1016/j.inffus.2022.07.005.

Article  Google Scholar 

Butrimas S, Driggers RG, Holst GC, Kopeika NS, Zilberman A. Effects of aerosol modulation transfer function on target identification. Opt Eng. 2020;59(7):1–14. https://doi.org/10.1117/1.OE.59.7.073103.

Article  Google Scholar 

Wang W, Zhou Z, Liu H, Xie G. MSDRN: pansharpening of multispectral images via multi-scale deep residual network. Remote Sens. 2021;13(6):1200. https://doi.org/10.3390/rs13061200.

Article  Google Scholar 

Zhang J, Pan J, Ren J, Song Y, Yang MH. Dynamic scene deblurring using spatially variant recurrent neural networks. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2018. p. 2521–2529. https://doi.org/10.1109/CVPR.2018.00267.

Tao X, Gao H, Shen X, Wang J, Jia J. Scale-recurrent network for deep image deblurring. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2018. p. 8174–8182. https://doi.org/10.1109/CVPR.2018.00853.

Cai B, Xu X, Jia K, Qing C, Tao D. Dehazenet: an end-to-end system for single image haze removal. IEEE Trans Image Process. 2016;25(11):5187–98. https://doi.org/10.1109/TIP.2016.2598681.

Article  MathSciNet  MATH  Google Scholar 

Ren W, Liu S, Zhang H, Pan J, Cao X, Yang M-H. Single image dehazing via multi-scale convolutional neural network. In: 2016 European Conference on Computer Vision(ECCV); 2016. p. 154–169. https://doi.org/10.1007/978-3-319-46475-6_10.

Zhang H, Patel VM. Densely connected pyramid dehazing network. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2018. p. 3194–3203. https://doi.org/10.1109/CVPR.2018.00337.

Guo C, Li C, Gou J, Loy CC, Hou J, Kwong S, Cong R. Zero-reference deep curve estimation for low-light image enhancement. In: 2020 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2020. p. 1780–1789. https://doi.org/10.1109/CVPR42600.2020.00185.

Li M, Liu J, Yang W, Sun X, Guo Z. Structure-revealing low-light image enhancement via robust Retinex model. IEEE Trans Image Process. 2018;27(6):2828–41. https://doi.org/10.1109/TIP.2018.2810539.

Article  MathSciNet  MATH  Google Scholar 

Quan R, Yu X, Liang Y, Yang Y. Removing raindrops and rain streaks in one go. In: 2021 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2021. p. 9147–9156. https://doi.org/10.1109/CVPR46437.2021.00903.

Wu H, Qu Y, Lin S, Zhou J, Qiao R, Zhang Z, Xie Y, Ma L. Contrastive learning for compact single image dehazing. In: 2021 IEEE Conference on Computer Vision and Pattern Recognition(CVPR); 2021. p. 10551–10560. https://doi.org/10.1109/CVPR.2021.01041.

Li X, Chen M, Nie F, Wang Q. A multiview-based parameter free framework for group detection. In: Proceedings of the AAAI Conference on Artificial Intelligence; 2017. p. 4147–4153. https://doi.org/10.1609/aaai.v31i1.11208.

Qi Y, Zhang S, Jiang F, Zhou H, Tao D, Li X. Siamese local and global networks for robust face tracking. IEEE Trans Image Process. 2020;29:9152–64. https://doi.org/10.1109/TIP.2020.3023621.

Article  MATH  Google Scholar 

Li X, Chen M, Wang Q. Quantifying and detecting collective motion in crowd scenes. IEEE Trans Image Process. 2020;29:5571–83. https://doi.org/10.1109/TIP.2020.2985284.

Article  MATH  Google Scholar 

Pan J, Lin Z, Su Z, Yang MH. Robust kernel estimation with outliers handling for image deblurring. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). 2016. https://doi.org/10.1109/CVPR.2016.306.

Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process. 2004;13(4):600–12. https://doi.org/10.1109/TIP.2003.819861.

Article  Google Scholar 

Mittal A, Moorthy AK, Bovik AC. No-reference image quality assessment in the spatial domain. IEEE Trans Image Process. 2012;21(12):4695–780. https://doi.org/10.1109/TIP.2012.2214050.

Article  MathSciNet  MATH  Google Scholar 

Mittal A, Fellow IEEE, Soundararajan R, Bovik AC. Making a “completely blind" image quality analyzer. IEEE Signal Process Lett. 2013;20(3):209–12. https://doi.org/10.1109/LSP.2012.2227726.