[1] Pentland A P. A new sense for depth of field[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 9, 523-531(1987).

[2] Bae S, Durand F. Defocus magnification[J]. Computer Graphics Forum, 26, 571-579(2007).

[3] Levin A, Lischinski D, Weiss Y. A closed-form solution to natural image matting[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30, 228-242(2008).

[4] Fan H J, Feng Y Z, Wang T et al. New method of blurred radius detection in defocused image[J]. Journal of Computer Applications, 32, 1875-1878(2012).

[5] Feng Y Z, Zhang J N, Feng N Q. Estimating Gaussian kernel of defocused image based on parameter correction method[J]. Journal of Henan Normal University (Natural Science Edition), 41, 149-152(2013).

[6] Zhuo S J, Sim T. Defocus map estimation from a single image[J]. Pattern Recognition, 44, 1852-1858(2011).

[7] D'Andres L, Salvador J, Kochale A et al. Non-parametric blur map regression for depth of field extension[J]. IEEE Transactions on Image Processing, 25, 1660-1673(2016).

[8] Persch N, Schroers C, Setzer S et al. Introducing more physics into variational depth-from-defocus[M]. Jiang X Y, Hornegger J, Koch R. German conference on pattern recognition. Lecture notes in computer science, 8753, 15-27(2014).

[9] Tang H X, Cohen S, Price B et al. Depth from defocus in the wild[C], 4773-4781(2017).

[10] Tai Y W, Brown M S. Single image defocus map estimation using local contrast prior[C], 1797-1800(2010).

[11] Zhu X, Cohen S, Schiller S et al. Estimating spatially varying defocus blur from a single image[J]. IEEE Transactions on Image Processing, 22, 4879-4891(2013).

[12] 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).

[13] Li H Y, Yang F, Tan W B et al. A self-adaptive clarity auto focus evaluation function based on HVS operator[J]. Infrared Technology, 39, 632-637(2017).

[14] Liu B, Qiao Q, Zhao J et al. 3D profile measurement based on depth from focus method using high-frequency component variance weighted entropy image sharpness evaluation function[J]. Infrared and Laser Engineering, 50, 210-218(2021).

[15] Yuan Y C, Hao J M. An algorithm for judging the depth of image defocusing used for infrared automatic focusing[J]. Infrared, 42, 33-40(2021).

[16] Lin Y, Zhang Z D, Liu J X et al. Gray image quality blind assessment based on morphological gradient[J]. Computer Applications and Software, 29, 264-266(2012).

[17] Cui G M, Zhang K Q, Mao L et al. Micro-image definition evaluation using multi-scale decomposition and gradient absolute value[J]. Opto-Electronic Engineering, 46, 59-69(2019).

[18] Liu J H, Xu M L, Xu X Y et al. Nonreference image quality evaluation algorithm based on wavelet convolutional neural network and information entropy[J]. Entropy, 21, 1070(2019).

[19] Chen D J, Chen H T, Chang L W. Fast defocus map estimation[C], 3962-3966(2016).

[20] Zhuo S J, Sim T. On the Recovery of depth from a single defocused image[M]. Jiang X Y, Petkov N. Computer analysis of images and patterns. Lecture notes in computer science, 5702, 889-897(2009).

[21] Tang C, Hou C P, Song Z J. Depth recovery and refinement from a single image using defocus cues[J]. Journal of Modern Optics, 62, 441-448(2015).

[22] Tang C, Hou C P, Song Z J. Defocus map estimation from a single image via spectrum contrast[J]. Optics Letters, 38, 1706-1708(2013).

[23] Liu R T, Li Z R, Jia J Y. Image partial blur detection and classification[C](2008).

[24] Shi J P, Xu L, Jia J Y. Discriminative blur detection features[C], 2965-2972(2014).

[25] Mavridaki E, Mezaris V. No-reference blur assessment in natural images using Fourier transform and spatial Pyramids[C], 566-570(2015).

[26] Otsu N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 9, 62-66(1979).