[1] Xu D. Hyperspectral remote sensing image denoising based on multiple linear regression and sparse representation[D]. Changsha: National University of Defense Technology(2013).

[2] Tan Z G, Ou J P, Zhang J et al. A laminar denoising algorithm for depth image[J]. Acta Optica Sinica, 37, 0510002(2017).

[3] Zhang X, Jing X L. A method for image denoising based on normal inverse Gaussian model using Bayesian estimation[J]. Acta Optica Sinica, 30, 70-74(2010).

[4] Pang S L. Research on image ambiguity evaluation Xi'an:[D]. Xidian University(2010).

[5] Lu H M, Xu M, Li X. Image deblurring with adaptive signal-noise ratio estimation for computational imaging system[J]. Acta Optica Sinica, 34, 0810002(2014).

[6] Feng S Y, Zhang N, Shen J et al. Method of cloud detection with hyperspectral remote sensing image based on the reflective characteristics[J]. China Optics, 8, 198-204(2015).

[7] Chen Y, Fan R S, Wang J X et al. Cloud detection of ZY-3 satellite remote sensing images based on deep learning[J]. Acta Optica Sinica, 38, 0128005(2018).

[8] Jiang X H, Wang X H, Ye H H et al. Cloud contaminated satellite data processing method in CO2 retrieving[J]. Acta Optica Sinica, 35, 0801001(2015).

[9] Gao L L, Liu J J, Ren X et al. Image quality evaluation of panoramic camera steropair based on structural similarity[J]. Laser & Optoelectronics Progress, 51, 071004(2014).

[10] Hou C P, Ma T T, Yue G H et al. Multiply-distorted image quality assessment based on high-order phase congruency[J]. Laser & Optoelectronics Progress, 54, 071001(2017).

[11] Zhang F, Zhang N Y, Li Z Z. Image quality evaluation method based on symmetric phase consistency[J]. Laser & Optoelectronics Progress, 54, 101003(2017).

[12] Wang Z M. Review of no-reference image quality assessment[J]. Acta Automatica Sinica, 41, 1062-1079(2015).

[13] Yin Y. Non-reference blur image quality assessment based on general regression neural network[J]. Laser & Infrared, 43, 466-470(2013).

[14] Zhu X L, Xu M Z, Cong M. Assessment method for no-reference remote sensing image quality based on support vector machine[J]. Spacecraft Recovery & Remote Sensing, 35, 83-90(2014).

[15] Wu Y Q, Zhou Y, Long Y L. Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM[J]. Acta Optica Sinica, 35, 0928001(2015).

[16] Fan C L. Hyperspectral remote sensing image classification algorithm based on decision tree[D]. Qinhuangdao: Yanshan University(2014).

[17] Zhou Y J, Tian Q J. Image quality evaluation of EO-1 hyperion sensor[J]. Geo-Information Science, 10, 678-683(2008).

[18] Yan L, Hu X B. Image quality assessment of IKONOS images based on contourlet-SIIM model[J]. Geomatics and Information Science of Wuhan University, 39, 12-16(2014).

[19] Zhang X L, Liu Z F, Dai J B et al. Image quality assessment based on visual perception and gradient structural similarity[J]. Application Research of Computers, 28, 2348-2351(2011).

[20] Qian F, Sun T, Guo J et al. Dynamic assessment of laser-dazzling effects based on the character of laser-spot and image feature[J]. Chinese Journal of Lasers, 41, 0609004(2014).

[21] Wang F, Ni J P, Dong T et al. No-reference image quality assessment method based on visual attention mechanism and sharpness metric approach[J]. Journal of Applied Optics, 39, 51-56(2018).

[22] Li S. Research on remote sensing image quality evaluation method based on statistical distribution Xi'an:[D]. Xidian University(2017).