[1] WANG Q H[M]. 3D Display Technology and Device(2011).

[2] JUNG S M, KANG H, LEE B Y et al. Numerical simulation of the displayed image on the entire screen of autostereoscopic displays[J]. Optics Express, 23, 7842-7855(2015).

[3] PANG B, SANG X Z, XING S J et al. High-efficient rendering of the multi-view image for the three-dimensional display based on the backward ray-tracing technique[J]. Optics Communications, 405, 306-311(2017).

[5] CHEN Y Y. Research on optimization method of integral imaging 3D display based on visualization simulation[D](2022).

[6] ZHANG S, XING S J, YU X B et al. A visual simulation method for 3D displays with dense views and experimental verification[J]. Optics Communications, 569, 130662(2024).

[7] WANDELL B A[M]. Foundations of Vision(1995).

[8] WANG Z, SIMONCELLI E P, BOVIK A C. Multiscale structural similarity for image quality assessment[C], 1398-1402(2003).

[9] WANG Z, LI Q. Information content weighting for perceptual image quality assessment[J]. IEEE Transactions on Image Processing, 20, 1185-1198(2011).

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

[11] ZHANG B, SANDER P V, BERMAK A. Gradient magnitude similarity deviation on multiple scales for color image quality assessment[C], 1253-1257(2017).

[12] BALANOV A, SCHWARTZ A, MOSHE Y et al. Image quality assessment based on DCT subband similarity[C], 2105-2109(2015).

[13] REISENHOFER R, BOSSE S, KUTYNIOK G et al. A Haar wavelet-based perceptual similarity index for image quality assessment[J]. Signal Processing: Image Communication, 61, 33-43(2018).

[14] NAFCHI H Z, SHAHKOLAEI A, HEDJAM R et al. Mean deviation similarity index: efficient and reliable full-reference image quality evaluator[J]. IEEE Access, 4, 5579-5590(2016).

[15] ZHANG R, ISOLA P, EFROS A A et al. The unreasonable effectiveness of deep features as a perceptual metric[C], 586-595(2018).

[16] DING K Y, MA K D, WANG S Q et al. Image quality assessment: Unifying structure and texture similarity[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 2567-2581(2022).

[17] PONOMARENKO N, JIN L N, IEREMEIEV O et al. Image database TID2013: peculiarities, results and perspectives[J]. Signal Processing: Image Communication, 30, 57-77(2015).

[18] 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, 15, 3440-3451(2006).

[19] LARSON E C, CHANDLER D M. Most apparent distortion: full-reference image quality assessment and the role of strategy[J]. Journal of Electronic Imaging, 19, 011006(2010).

[20] CUI J X, YANG B. Survey on Bayesian optimization methodology and applications[J]. Journal of Software, 29, 3068-3090(2018).

[21] SHAHRIARI B, SWERSKY K, WANG Z et al. Taking the human out of the loop: a review of Bayesian optimization[J]. Proceedings of the IEEE, 104, 148-175(2016).

[22] ZHANG Y J, LI S M, WEI J J et al. Subjective quality evaluation method of stereo image[J]. Acta Photonica Sinica, 41, 602-607(2012).

[23] ZHANG L, LI H Y. SR-SIM: a fast and high performance IQA index based on spectral residual[C], 1473-1476(2012).

[24] GATYS L A, ECKER A S, BETHGE M. A neural algorithm of artistic style[J/OL]. arXiv, 1508-06576(2015).