[1] 薛小波, 郁梅, 何美伶. 基于仿视觉细胞模型的立体图像质量评价方法[J]. 激光与光电子学进展, 2016, 53(4): 041004.

    Xue X B, Yu M, He M L. Stereoscopic image-quality-assessment method based on visual cell model[J]. Laser & Optoelectronics Progress, 2016, 53(4): 041004.

[2] Sheikh H R, Sabir M F, Bovik A C. A statistical evaluation of recent full reference image quality assessment algorithms[J]. IEEE Transactions on Image Processing, 2006, 15(11): 3440-3451.

[3] Zhang L, Zhang L, Mou X Q, et al. FSIM: a feature similarity index for image quality assessment[J]. IEEE Transactions on Image Processing, 2011, 20(8): 2378-2386.

[4] Xue W F, Zhang L, Mou X Q, et al. Gradient magnitude similarity deviation: a highly efficient perceptual image quality index[J]. IEEE Transactions on Image Processing, 2014, 23(2): 684-695.

[5] Wang Z, Bovik A C, Sheikh H R, et al. Image quality assessment: from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 13(4): 600-612.

[6] WangZ, Simoncelli EP, Bovik AC. Multiscale structural similarity for image quality assessment[C]∥Proceedings of IEEE Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, 2003, 2: 1398- 1402.

[7] Wang S Q, Ma K D, Yeganeh H, et al. A patch-structure representation method for quality assessment of contrast changed images[J]. IEEE Signal Processing Letters, 2015, 22(12): 2387-2390.

[8] Fang Y M, Ma K D, Wang Z, et al. No-reference quality assessment of contrast-distorted images based on natural scene statistics[J]. IEEE Signal Processing Letters, 2014, 22(7): 838-842.

[9] Mittal A, Soundararajan R, Bovik A C. Making a“completely blind” image quality analyzer[J]. IEEE Signal Processing Letters, 2013, 20(3): 209-212.

[10] Zhang Y, Chandler D M. No-reference image quality assessment based on log-derivative statistics of natural scenes[J]. Journal of Electronic Imaging, 2013, 22(4): 043025.

[11] Romeny B MH. Front-end vision and multi-scale image analysis: multi-scale computer vision theory and applications, written in mathematica[M]. New York: Springer Science & Business Media, 2008: 1- 177.

[12] Nercessian S C, Panetta K A, Agaian S S. Non-linear direct multi-scale image enhancement based on the luminance and contrast masking characteristics of the human visual system[J]. IEEE Transactions on Image Processing, 2013, 22(9): 3549-3561.

[13] Marĉelja S. Mathematical description of the responses of simple cortical cells[J]. Journal of the Optical Society of America, 1980, 70(11): 1297-1300.

[14] 杨作廷, 阮萍, 翟波. 基于图像熵的高动态范围场景的自动曝光算法[J]. 光子学报, 2013, 42(6): 742-746.

    Yang Z T, Ruan P, Zhai B. Auto-exposure algorithm for scenes with high dynamic range based on image entropy[J]. Acta Photonica Sinica, 2013, 42(6): 742-746.

[15] Narwaria M, Lin W S. SVD-based quality metric for image and video using machine learning[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2012, 42(2): 347-364.

[16] Video Quality ExpertsGroup. Final report from the Video Quality Experts Group on the validation of objective models of video quality assessment, Phase II (FR_TV2)[EB/OL]. [2018-04-16].http:∥www.vqeg.org/, 2003.

[17] Li L D, Xia W H, Lin W S, et al. No-reference and robust image sharpness evaluation based on multiscale spatial and spectral features[J]. IEEE Transactions on Multimedia, 2017, 19(5): 1030-1040.

[18] YeP, KumarJ, KangL, et al. Unsupervised feature learning framework for no-reference image quality assessment[C]∥Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012: 1098- 1105.

[19] Moorthy A K, Bovik A C. A two-step framework for constructing blind image quality indices[J]. IEEE Signal Processing Letters, 2010, 17(5): 513-516.

[20] Mittal A, Moorthy A K, Bovik A C. No-reference image quality assessment in the spatial domain[J]. IEEE Transactions on Image Processing, 2012, 21(12): 4695-4708.

[21] Moorthy A K, Bovik A C. Blind image quality assessment: from natural scene statistics to perceptual quality[J]. IEEE Transactions on Image Processing, 2011, 20(12): 3350-3364.

[22] Saad M A, Bovik A C, Charrier C. Blind image quality assessment:a natural scene statistics approach in the DCT domain[J]. IEEE Transactions on Image Processing, 2012, 21(8): 3339-3352.

[23] Liu L X, Liu B, Huang H, et al. No-reference image quality assessment based on spatial and spectral entropies[J]. Signal Processing: Image Communication, 2014, 29(8): 856-863.

[24] Xue WF, ZhangL, Mou XQ. Learning without human scores for blind image quality assessment[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2013: 995- 1002.