{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T21:08:06Z","timestamp":1792530486377,"version":"4.5.0"},"reference-count":106,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2021,1,21]],"date-time":"2021-01-21T00:00:00Z","timestamp":1611187200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,21]],"date-time":"2021-01-21T00:00:00Z","timestamp":1611187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1007\/s11263-020-01419-7","type":"journal-article","created":{"date-parts":[[2021,1,21]],"date-time":"2021-01-21T05:03:11Z","timestamp":1611205391000},"page":"1258-1281","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":218,"title":["Comparison of Full-Reference Image Quality Models for Optimization of Image Processing Systems"],"prefix":"10.1007","volume":"129","author":[{"given":"Keyan","family":"Ding","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8608-1128","authenticated-orcid":false,"given":"Kede","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiqi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eero P.","family":"Simoncelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,1,21]]},"reference":[{"key":"1419_CR1","doi-asserted-by":"crossref","unstructured":"Agustsson, E., Tschannen, M., Mentzer, F., Timofte, R., & Gool, L. V. (2019). Generative adversarial networks for extreme learned image compression. In IEEE conference on computer vision and pattern recognition (pp. 221\u2013231).","DOI":"10.1109\/ICCV.2019.00031"},{"key":"1419_CR2","doi-asserted-by":"crossref","unstructured":"Ball\u00e9, J., Laparra, V., & Simoncelli, E. P. (2016) End-to-end optimization of nonlinear transform codes for perceptual quality. In Picture coding symposium (pp. 1\u20135).","DOI":"10.1109\/PCS.2016.7906310"},{"key":"1419_CR3","unstructured":"Ball\u00e9, J., Laparra, V., & & Simoncelli, E. P. (2017). End-to-end optimized image compression. In International conference on learning representations (pp. 1\u201327)."},{"key":"1419_CR4","unstructured":"Ball\u00e9, J., Minnen, D., Singh, S., Hwang, S. J., & Johnston, N. (2018) Variational image compression with a scale hyperprior. In International conference on learning representations (pp. 1\u201347)."},{"key":"1419_CR5","doi-asserted-by":"crossref","unstructured":"Blau, Y., & Michaeli, T. (2018). The perception\u2013distortion tradeoff. In IEEE conference on computer vision and pattern recognition (pp. 6228\u20136237).","DOI":"10.1109\/CVPR.2018.00652"},{"issue":"1","key":"1419_CR6","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/TIP.2017.2760518","volume":"27","author":"S Bosse","year":"2018","unstructured":"Bosse, S., Maniry, D., M\u00fcller, K. R., Wiegand, T., & Samek, W. (2018). Deep neural networks for no-reference and full-reference image quality assessment. IEEE Transactions on Image Processing, 27(1), 206\u2013219.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"3\/4","key":"1419_CR7","doi-asserted-by":"publisher","first-page":"324","DOI":"10.2307\/2334029","volume":"39","author":"RA Bradley","year":"1952","unstructured":"Bradley, R. A., & Terry, M. E. (1952). Rank analysis of incomplete block designs: I. The method of paired comparisons. Biometrika, 39(3\/4), 324\u2013345.","journal-title":"Biometrika"},{"issue":"4","key":"1419_CR8","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1109\/TCOM.1983.1095851","volume":"31","author":"P Burt","year":"1983","unstructured":"Burt, P., & Adelson, E. (1983). The Laplacian pyramid as a compact image code. IEEE Transactions on Communications, 31(4), 532\u2013540.","journal-title":"IEEE Transactions on Communications"},{"issue":"10","key":"1419_CR9","doi-asserted-by":"publisher","first-page":"4007","DOI":"10.1109\/TIP.2013.2266579","volume":"22","author":"HW Chang","year":"2013","unstructured":"Chang, H. W., Yang, H., Gan, Y., & Wang, M. H. (2013). Sparse feature fidelity for perceptual image quality assessment. IEEE Transactions on Image Processing, 22(10), 4007\u20134018.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR10","doi-asserted-by":"crossref","unstructured":"Channappayya, S. S., Bovik, A. C., Caramanis, C., & Heath, R. W. (2008). SSIM-optimal linear image restoration. In IEEE international conference on acoustics, speech, and signal processing (pp. 765\u2013768).","DOI":"10.1109\/ICASSP.2008.4517722"},{"issue":"8","key":"1419_CR11","doi-asserted-by":"publisher","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","volume":"16","author":"K Dabov","year":"2007","unstructured":"Dabov, K., Foi, A., Katkovnik, V., & Egiazarian, K. (2007). Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Transactions on Image Processing, 16(8), 2080\u20132095.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR12","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1117\/12.135952","volume":"3","author":"SJ Daly","year":"1992","unstructured":"Daly, S. J. (1992). Visible differences predictor: An algorithm for the assessment of image fidelity. Human Vision, Visual Processing, and Digital Display, 3, 2\u201315.","journal-title":"Human Vision, Visual Processing, and Digital Display"},{"key":"1419_CR13","doi-asserted-by":"crossref","unstructured":"Ding, K., Ma, K., Wang, S., & Simoncelli, E. P. (2020). Image quality assessment: Unifying structure and texture similarity. CoRR arXiv:2004.07728.","DOI":"10.1109\/TPAMI.2020.3045810"},{"key":"1419_CR14","doi-asserted-by":"crossref","unstructured":"Dong, C., Loy, C. C., He, K., & Tang, X. (2014). Learning a deep convolutional network for image super-resolution. In European conference on computer vision (pp. 184\u2013199).","DOI":"10.1007\/978-3-319-10593-2_13"},{"issue":"432","key":"1419_CR15","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1080\/01621459.1995.10476626","volume":"90","author":"DL Donoho","year":"1995","unstructured":"Donoho, D. L., & Johnstone, I. M. (1995). Adapting to unknown smoothness via wavelet shrinkage. Journal of the American Statistical Association, 90(432), 1200\u20131224.","journal-title":"Journal of the American Statistical Association"},{"key":"1419_CR16","doi-asserted-by":"crossref","unstructured":"Egiazarian, K., Ponomarenko, M., Lukin, V., & Ieremeiev, O. (2018). Statistical evaluation of visual quality metrics for image denoising. In IEEE International conference on acoustics, speech and signal processing (pp. 6752\u20136756).","DOI":"10.1109\/ICASSP.2018.8462294"},{"issue":"12","key":"1419_CR17","doi-asserted-by":"publisher","first-page":"3736","DOI":"10.1109\/TIP.2006.881969","volume":"15","author":"M Elad","year":"2006","unstructured":"Elad, M., & Aharon, M. (2006). Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing, 15(12), 3736\u20133745.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"7","key":"1419_CR18","first-page":"838","volume":"22","author":"Y Fang","year":"2015","unstructured":"Fang, Y., Ma, K., Wang, Z., Lin, W., Fang, Z., & Zhai, G. (2015). No-reference quality assessment of contrast-distorted images based on natural scene statistics. IEEE Signal Processing Letters, 22(7), 838\u2013842.","journal-title":"IEEE Signal Processing Letters"},{"issue":"3","key":"1419_CR19","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1145\/1141911.1141956","volume":"25","author":"R Fergus","year":"2006","unstructured":"Fergus, R., Singh, B., Hertzmann, A., Roweis, S. T., & Freeman, W. T. (2006). Removing camera shake from a single photograph. ACM Transactions on Graphics, 25(3), 787\u2013794.","journal-title":"ACM Transactions on Graphics"},{"key":"1419_CR20","volume-title":"What\u2019s wrong with mean-squared error?","author":"B Girod","year":"1993","unstructured":"Girod, B. (1993). What\u2019s wrong with mean-squared error?. Cambridge, MA: MIT Press."},{"key":"1419_CR21","doi-asserted-by":"crossref","unstructured":"Glasner, D., Bagon, S., & Irani, M. (2009). Super-resolution from a single image. In IEEE international conference on computer vision (pp. 349\u20133560).","DOI":"10.1109\/ICCV.2009.5459271"},{"key":"1419_CR22","first-page":"356","volume":"9599","author":"SA Golestaneh","year":"2015","unstructured":"Golestaneh, S. A., Subedar, M. M., & Karam, L. J. (2015). The effect of texture granularity on texture synthesis quality. Applications of Digital Image Processing XXXVIII, 9599, 356\u2013361.","journal-title":"Applications of Digital Image Processing XXXVIII"},{"key":"1419_CR23","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014) Generative adversarial nets. InConference on neural information processing systems (pp. 2672\u20132680)."},{"key":"1419_CR24","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/S0065-2458(08)60436-2","volume":"10","author":"U Grenander","year":"1970","unstructured":"Grenander, U. (1970). A unified approach to pattern analysis. Advances in Computers, 10, 175\u2013216.","journal-title":"Advances in Computers"},{"issue":"4","key":"1419_CR25","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1109\/TIP.2008.917204","volume":"17","author":"Y Hel-Or","year":"2008","unstructured":"Hel-Or, Y., & Shaked, D. (2008). A discriminative approach for wavelet denoising. IEEE Transactions on Image Processing, 17(4), 443\u2013457.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR26","doi-asserted-by":"crossref","unstructured":"Huang, J. B., Singh, A., & Ahuja, N. (2015). Single image super-resolution from transformed self-exemplars. In IEEE conference on computer vision and pattern recognition (pp. 5197\u20135206).","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"1419_CR27","volume-title":"Methodology for the subjective assessment of the quality of television pictures","author":"ITU-R","year":"2002","unstructured":"ITU-R. (2002). Methodology for the subjective assessment of the quality of television pictures. Geneva: International Telecommunication Union."},{"key":"1419_CR28","doi-asserted-by":"crossref","unstructured":"Johnson, J., Alahi, A., & Li, F. F. (2016). Perceptual losses for real-time style transfer and super-resolution. In European conference on computer vision (pp. 694\u2013711).","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"1419_CR29","first-page":"228","volume":"2","author":"C Jordan","year":"1881","unstructured":"Jordan, C. (1881). Sur la s\u00e9rie de fourier. Comptes Rendus de l\u2019Acad\u00e9mie des Sciences Paris, 2, 228\u2013230.","journal-title":"Comptes Rendus de l\u2019Acad\u00e9mie des Sciences Paris"},{"key":"1419_CR30","unstructured":"Kingma, D. P., & Ba, J. (2015). Adam: A method for stochastic optimization. In International conference on learning representations (pp. 1\u201315)."},{"key":"1419_CR31","doi-asserted-by":"crossref","unstructured":"K\u00f6hler, R., Hirsch, M., Mohler, B., Sch\u00f6lkopf, B., & Harmeling, S. (2012). Recording and playback of camera shake: Benchmarking blind deconvolution with a real-world database. In European conference on computer vision (pp. 27\u201340).","DOI":"10.1007\/978-3-642-33786-4_3"},{"issue":"3","key":"1419_CR32","first-page":"1","volume":"1","author":"P Kovesi","year":"1999","unstructured":"Kovesi, P. (1999). Image features from phase congruency. Journal of Computer Vision Research, 1(3), 1\u201326.","journal-title":"Journal of Computer Vision Research"},{"key":"1419_CR33","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., & Matas, J. (2018). DeblurGAN: Blind motion deblurring using conditional adversarial networks. In IEEE conference on computer vision and pattern recognition (pp. 8183\u20138192).","DOI":"10.1109\/CVPR.2018.00854"},{"key":"1419_CR34","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Martyniuk, T., Wu, J., & Wang, Z. (2019). DeblurGAN-v2: Deblurring (orders-of-magnitude) faster and better. In IEEE international conference on computer vision (pp. 8878\u20138887).","DOI":"10.1109\/ICCV.2019.00897"},{"key":"1419_CR35","doi-asserted-by":"crossref","unstructured":"Lai, W. S., Huang, J. B., Hu, Z., Ahuja, N., & Yang, M. H. (2016). A comparative study for single image blind deblurring. In IEEE conference on computer vision and pattern recognition (pp. 1701\u20131709).","DOI":"10.1109\/CVPR.2016.188"},{"key":"1419_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2352\/ISSN.2470-1173.2016.16.HVEI-103","volume":"16","author":"V Laparra","year":"2016","unstructured":"Laparra, V., Ball\u00e9, J., Berardino, A., & Simoncelli, E. P. (2016). Perceptual image quality assessment using a normalized Laplacian pyramid. Electronic Imaging, 16, 1\u20136.","journal-title":"Electronic Imaging"},{"issue":"9","key":"1419_CR37","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1364\/JOSAA.34.001511","volume":"34","author":"V Laparra","year":"2017","unstructured":"Laparra, V., Berardino, A., Ball\u00e9, J., & Simoncelli, E. P. (2017). Perceptually optimized image rendering. Journal of the Optical Society of America A, 34(9), 1511\u20131525.","journal-title":"Journal of the Optical Society of America A"},{"issue":"1","key":"1419_CR38","first-page":"1","volume":"19","author":"EC Larson","year":"2010","unstructured":"Larson, E. C., & Chandler, D. M. (2010). Most apparent distortion: Full-reference image quality assessment and the role of strategy. Journal of Electronic Imaging, 19(1), 1\u201321.","journal-title":"Journal of Electronic Imaging"},{"key":"1419_CR39","doi-asserted-by":"crossref","unstructured":"Ledig, C., Theis, L., Husz\u00e1r, F., Caballero, J., Cunningham, A., & Acosta, A., et al. (2017). Photo-realistic single image super-resolution using a generative adversarial network. In IEEE conference on computer vision and pattern recognition (pp. 4681\u20134690).","DOI":"10.1109\/CVPR.2017.19"},{"issue":"10","key":"1419_CR40","doi-asserted-by":"publisher","first-page":"1521","DOI":"10.1109\/83.951537","volume":"10","author":"X Li","year":"2001","unstructured":"Li, X., & Orchard, M. T. (2001). New edge-directed interpolation. IEEE Transactions on Image Processing, 10(10), 1521\u20131527.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR41","doi-asserted-by":"crossref","unstructured":"Lim, B., Son, S., Kim, H., Nah, S., & Mu\u00a0Lee, K. (2017). Enhanced deep residual networks for single image super-resolution. In IEEE conference on computer vision and pattern recognition workshop (pp. 136\u2013144).","DOI":"10.1109\/CVPRW.2017.151"},{"issue":"4","key":"1419_CR42","doi-asserted-by":"publisher","first-page":"1500","DOI":"10.1109\/TIP.2011.2175935","volume":"21","author":"A Liu","year":"2012","unstructured":"Liu, A., Lin, W., & Narwaria, M. (2012a). Image quality assessment based on gradient similarity. IEEE Transactions on Image Processing, 21(4), 1500\u20131512.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"5","key":"1419_CR43","doi-asserted-by":"publisher","first-page":"1793","DOI":"10.1109\/TIP.2012.2236343","volume":"22","author":"TJ Liu","year":"2012","unstructured":"Liu, T. J., Lin, W., & Kuo, C. C. J. (2012b). Image quality assessment using multi-method fusion. IEEE Transactions on Image Processing, 22(5), 1793\u20131807.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"6","key":"1419_CR44","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1145\/2508363.2508391","volume":"32","author":"Y Liu","year":"2013","unstructured":"Liu, Y., Wang, J., Cho, S., Finkelstein, A., & Rusinkiewicz, S. (2013). A no-reference metric for evaluating the quality of motion deblurring. ACM Transactions on Graphics, 32(6), 175\u2013186.","journal-title":"ACM Transactions on Graphics"},{"key":"1419_CR45","volume-title":"The use of psychophysical data and models in the analysis of display system performance","author":"J Lubin","year":"1993","unstructured":"Lubin, J. (1993). The use of psychophysical data and models in the analysis of display system performance. Cambridge, MA: MIT Press."},{"key":"1419_CR46","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1086\/111605","volume":"79","author":"LB Lucy","year":"1974","unstructured":"Lucy, L. B. (1974). An iterative technique for the rectification of observed distributions. Astronomical Journal, 79, 745.","journal-title":"Astronomical Journal"},{"key":"1419_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cviu.2016.12.009","volume":"158","author":"C Ma","year":"2017","unstructured":"Ma, C., Yang, C. Y., Yang, X., & Yang, M. H. (2017a). Learning a no-reference quality metric for single-image super-resolution. Computer Vision and Image Understanding, 158, 1\u201316.","journal-title":"Computer Vision and Image Understanding"},{"key":"1419_CR48","doi-asserted-by":"crossref","unstructured":"Ma, K., Duanmu, Z., & Wang, Z. (2018). Geometric transformation invariant image quality assessment using convolutional neural networks. In IEEE international conference on acoustics, speech, and signal processing (pp. 6732\u20136736).","DOI":"10.1109\/ICASSP.2018.8462176"},{"issue":"4","key":"1419_CR49","doi-asserted-by":"publisher","first-page":"851","DOI":"10.1109\/TPAMI.2018.2889948","volume":"42","author":"K Ma","year":"2020","unstructured":"Ma, K., Duanmu, Z., Wang, Z., Wu, Q., Liu, W., Yong, H., et al. (2020). Group maximum differentiation competition: Model comparison with few samples. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(4), 851\u2013864.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"2","key":"1419_CR50","doi-asserted-by":"publisher","first-page":"1004","DOI":"10.1109\/TIP.2016.2631888","volume":"26","author":"K Ma","year":"2017","unstructured":"Ma, K., Duanmu, Z., Wu, Q., Wang, Z., Yong, H., Li, H., et al. (2017b). Waterloo exploration database: New challenges for image quality assessment models. IEEE Transactions on Image Processing, 26(2), 1004\u20131016.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR51","doi-asserted-by":"crossref","unstructured":"Ma, K., Liu, X., Fang, Y., & Simoncelli, E. P. (2019). Blind image quality assessment by learning from multiple annotators. In IEEE international conference on image processing (pp. 2344\u20132348).","DOI":"10.1109\/ICIP.2019.8803390"},{"issue":"10","key":"1419_CR52","doi-asserted-by":"publisher","first-page":"3086","DOI":"10.1109\/TIP.2015.2436340","volume":"24","author":"K Ma","year":"2015","unstructured":"Ma, K., Yeganeh, H., Zeng, K., & Wang, Z. (2015). High dynamic range image compression by optimizing tone mapped image quality index. IEEE Transactions on Image Processing, 24(10), 3086\u20133097.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR53","doi-asserted-by":"crossref","unstructured":"Mentzer, F., Agustsson, E., Tschannen, M., Timofte, R., & Van\u00a0Gool, L. (2018) Conditional probability models for deep image compression. In IEEE conference on computer vision and pattern recognition (pp. 4394\u20134402).","DOI":"10.1109\/CVPR.2018.00462"},{"issue":"9","key":"1419_CR54","doi-asserted-by":"publisher","first-page":"2319","DOI":"10.1109\/TMM.2019.2902097","volume":"21","author":"X Min","year":"2019","unstructured":"Min, X., Zhai, G., Gu, K., Zhu, Y., Zhou, J., Guo, G., et al. (2019). Quality evaluation of image dehazing methods using synthetic hazy images. IEEE Transactions on Multimedia, 21(9), 2319\u20132333.","journal-title":"IEEE Transactions on Multimedia"},{"key":"1419_CR55","doi-asserted-by":"crossref","unstructured":"Pan, J., Sun, D., Pfister, H., & Yang, M. H. (2016). Blind image deblurring using dark channel prior. In IEEE conference on computer vision and pattern recognition (pp. 1628\u20131636).","DOI":"10.1109\/CVPR.2016.180"},{"key":"1419_CR56","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.image.2014.10.009","volume":"30","author":"N Ponomarenko","year":"2015","unstructured":"Ponomarenko, N., Jin, L., Ieremeiev, O., Lukin, V., Egiazarian, K., Astola, J., et al. (2015). Image database TID2013: Peculiarities, results and perspectives. Signal Processing Image Communication, 30, 57\u201377.","journal-title":"Signal Processing Image Communication"},{"issue":"11","key":"1419_CR57","doi-asserted-by":"publisher","first-page":"1338","DOI":"10.1109\/TIP.2003.818640","volume":"12","author":"J Portilla","year":"2003","unstructured":"Portilla, J., Strela, V., Wainwright, M. J., & Simoncelli, E. P. (2003). Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE Transactions on Image Processing, 12(11), 1338\u20131351.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR58","doi-asserted-by":"crossref","unstructured":"Prashnani, E., Cai, H., Mostofi, Y., & Sen, P. (2018). PieAPP: Perceptual image-error assessment through pairwise preference. In IEEE conference on computer vision and pattern recognition (pp. 1808\u20131817).","DOI":"10.1109\/CVPR.2018.00194"},{"key":"1419_CR59","doi-asserted-by":"crossref","unstructured":"Rajashekar, U., Wang, Z., & Simoncelli, E. P. (2009). Quantifying color image distortions based on adaptive spatio-chromatic signal decompositions. In IEEE international conference on image processing, IEEE (pp. 2213\u20132216).","DOI":"10.1109\/ICIP.2009.5413889"},{"issue":"8","key":"1419_CR60","doi-asserted-by":"publisher","first-page":"1342","DOI":"10.1109\/TIP.2008.925392","volume":"17","author":"M Raphan","year":"2008","unstructured":"Raphan, M., & Simoncelli, E. P. (2008). Optimal denoising in redundant representations. IEEE Transactions on Image Processing, 17(8), 1342\u20131352.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"1","key":"1419_CR61","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1364\/JOSA.62.000055","volume":"62","author":"WH Richardson","year":"1972","unstructured":"Richardson, W. H. (1972). Bayesian-based iterative method of image restoration. Journal of Optical Society of America, 62(1), 55\u201359.","journal-title":"Journal of Optical Society of America"},{"key":"1419_CR62","doi-asserted-by":"crossref","unstructured":"Safranek, R. J., & Johnston, J. D. (1989). A perceptually tuned sub-band image coder with image dependent quantization and post-quantization data compression. In IEEE international conference on acoustics, speech, and signal processing (pp. 1945\u20131948).","DOI":"10.1109\/ICASSP.1989.266837"},{"issue":"3","key":"1419_CR63","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","volume":"27","author":"CE Shannon","year":"1948","unstructured":"Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379\u2013423.","journal-title":"Bell System Technical Journal"},{"issue":"2","key":"1419_CR64","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1109\/TIP.2005.859378","volume":"15","author":"HR Sheikh","year":"2006","unstructured":"Sheikh, H. R., & Bovik, A. C. (2006). Image information and visual quality. IEEE Transactions on Image Processing, 15(2), 430\u2013444.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"12","key":"1419_CR65","doi-asserted-by":"publisher","first-page":"2117","DOI":"10.1109\/TIP.2005.859389","volume":"14","author":"HR Sheikh","year":"2005","unstructured":"Sheikh, H. R., Bovik, A. C., & De Veciana, G. (2005). An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Transactions on Image Processing, 14(12), 2117\u20132128.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR66","unstructured":"Sheikh, H. R., Wang, Z., Bovik, A. C., & Cormack, L. (2006). Image and video quality assessment research at LIVE. http:\/\/live.ece.utexas.edu\/research\/quality\/."},{"key":"1419_CR67","doi-asserted-by":"crossref","unstructured":"Shi, W., Caballero, J., Husz\u00e1r, F., Totz, J., Aitken, A. P., Bishop, R., Rueckert, D., & Wang, Z. (2016). Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In IEEE conference on computer vision and pattern recognition (pp. 1874\u20131883).","DOI":"10.1109\/CVPR.2016.207"},{"key":"1419_CR68","doi-asserted-by":"crossref","unstructured":"Simoncelli, E. P., & Adelson, E. H. (1996). Noise removal via bayesian wavelet coring. In IEEE international conference on image processing, IEEE (Vol. 1, pp. 379\u2013382).","DOI":"10.1109\/ICIP.1996.559512"},{"key":"1419_CR69","unstructured":"Simonyan, K., & Zisserman, A. (2015). Very deep convolutional networks for large-scale image recognition. In International conference on learning representations (pp. 1\u201314)."},{"key":"1419_CR70","doi-asserted-by":"crossref","unstructured":"Snell, J., Ridgeway, K., Liao, R., Roads, B.D., Mozer, M.C., & Zemel, R.S. (2017). Learning to generate images with perceptual similarity metrics. In: IEEE Transactions on Image Processing, pp 4277\u20134281","DOI":"10.1109\/ICIP.2017.8297089"},{"key":"1419_CR71","doi-asserted-by":"crossref","unstructured":"Sun, J., Xu, Z., & Shum, H. Y. (2008). Image super-resolution using gradient profile prior. In ieee conference on computer vision and pattern recognition, IEEE (pp. 1\u20138).","DOI":"10.1109\/CVPR.2008.4587659"},{"key":"1419_CR72","unstructured":"Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., & Fergus, R. (2013). Intriguing properties of neural networks. In International conference on learning representations (pp. 1\u201310)."},{"key":"1419_CR73","doi-asserted-by":"crossref","unstructured":"Tao, X., Gao, H., Shen, X., Wang, J., & Jia, J. (2018). Scale-recurrent network for deep image deblurring. In IEEE conference on computer vision and pattern recognition (pp. 8174\u20138182).","DOI":"10.1109\/CVPR.2018.00853"},{"key":"1419_CR74","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1117\/12.172664","volume":"2179","author":"PC Teo","year":"1994","unstructured":"Teo, P. C., & Heeger, D. J. (1994). Perceptual image distortion. Human Vision, Visual Processing, and Digital Display V, 2179, 127\u2013141.","journal-title":"Human Vision, Visual Processing, and Digital Display V"},{"issue":"5","key":"1419_CR75","doi-asserted-by":"publisher","first-page":"1235","DOI":"10.1109\/TMM.2018.2875307","volume":"21","author":"S Tian","year":"2018","unstructured":"Tian, S., Zhang, L., Morin, L., & D\u00e9forges, O. (2018). A benchmark of DIBR synthesized view quality assessment metrics on a new database for immersive media applications. IEEE Transactions on Multimedia, 21(5), 1235\u20131247.","journal-title":"IEEE Transactions on Multimedia"},{"key":"1419_CR76","doi-asserted-by":"crossref","unstructured":"Timofte, R., De\u00a0Smet, V., & Van\u00a0Gool, L. (2013). Anchored neighborhood regression for fast example-based super-resolution. In IEEE international conference on computer vision (pp. 1920\u20131927).","DOI":"10.1109\/ICCV.2013.241"},{"key":"1419_CR77","doi-asserted-by":"crossref","unstructured":"Timofte, R., Agustsson, E., Van\u00a0Gool, L., Yang, M. H., & Zhang, L. (2017). NTIRE 2017 challenge on single image super-resolution: Methods and results. In IEEE conference on computer vision and pattern recognition (pp. 114\u2013125).","DOI":"10.1109\/CVPRW.2017.150"},{"key":"1419_CR78","doi-asserted-by":"crossref","unstructured":"Tomasi, C., & Manduchi, R. (1998). Bilateral filtering for gray and color images. In IEEE international conference on computer vision, IEEE (pp. 839\u2013846).","DOI":"10.1109\/ICCV.1998.710815"},{"key":"1419_CR79","doi-asserted-by":"crossref","unstructured":"Ulyanov, D., Vedaldi, A., & Lempitsky, V. (2018). Deep image prior. In IEEE conference on computer vision and pattern recognition (pp. 9446\u20139454).","DOI":"10.1109\/CVPR.2018.00984"},{"issue":"6","key":"1419_CR80","doi-asserted-by":"publisher","first-page":"1105","DOI":"10.1109\/TMM.2009.2026096","volume":"11","author":"V Vukadinovic","year":"2009","unstructured":"Vukadinovic, V., & Karlsson, G. (2009). Trade-offs in bit-rate allocation for wireless video streaming. IEEE Transactions on Multimedia, 11(6), 1105\u20131113.","journal-title":"IEEE Transactions on Multimedia"},{"issue":"12","key":"1419_CR81","doi-asserted-by":"publisher","first-page":"2387","DOI":"10.1109\/LSP.2015.2487369","volume":"22","author":"S Wang","year":"2015","unstructured":"Wang, S., Ma, K., Yeganeh, H., Wang, Z., & Lin, W. (2015). A patch-structure representation method for quality assessment of contrast changed images. IEEE Signal Processing Letters, 22(12), 2387\u20132390.","journal-title":"IEEE Signal Processing Letters"},{"issue":"4","key":"1419_CR82","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1109\/TCSVT.2011.2168269","volume":"22","author":"S Wang","year":"2011","unstructured":"Wang, S., Rehman, A., Wang, Z., Ma, S., & Gao, W. (2011). SSIM-motivated rate-distortion optimization for video coding. IEEE Transactions on Circuits and Systems for Video Technology, 22(4), 516\u2013529.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"1419_CR83","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.sigpro.2015.11.011","volume":"45","author":"T Wang","year":"2016","unstructured":"Wang, T., Zhang, L., Jia, H., Li, B., & Shu, H. (2016). Multiscale contrast similarity deviation: An effective and efficient index for perceptual image quality assessment. Signal Processing: Image Communication, 45, 1\u20139.","journal-title":"Signal Processing: Image Communication"},{"key":"1419_CR84","doi-asserted-by":"crossref","unstructured":"Wang, X., Yu, K., Wum S., Gu, J., Liu, Y., & Dong, C.(2018). ESRGAN: Enhanced super-resolution generative adversarial networks. In European conference on computer vision workshops","DOI":"10.1007\/978-3-030-11021-5_5"},{"issue":"6","key":"1419_CR85","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1109\/MSP.2011.942471","volume":"28","author":"Z Wang","year":"2011","unstructured":"Wang, Z., & Bovik, A. C. (2011). Reduced- and no-reference image quality assessment: The natural scene statistic model approach. IEEE Signal Processing Magazine, 28(6), 29\u201340.","journal-title":"IEEE Signal Processing Magazine"},{"issue":"4","key":"1419_CR86","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4), 600\u2013612.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR87","unstructured":"Wang, Z., & Simoncelli, E. P. (2005). Translation insensitive image similarity in complex wavelet domain. In IEEE international conference on acoustics, speech, and signal processing (pp. 573\u2013576)."},{"issue":"12","key":"1419_CR88","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1167\/8.12.8","volume":"8","author":"Z Wang","year":"2008","unstructured":"Wang, Z., & Simoncelli, E. P. (2008). Maximum differentiation (MAD) competition: A methodology for comparing computational models of perceptual quantities. Journal of Vision, 8(12), 1\u201313.","journal-title":"Journal of Vision"},{"key":"1419_CR89","doi-asserted-by":"crossref","unstructured":"Wang, Z., Simoncelli, E. P., & Bovik, A. C. (2003). Multiscale structural similarity for image quality assessment. In IEEE Asilomar conference on signals, system and computers (pp. 1398\u20131402).","DOI":"10.1109\/ACSSC.2003.1292216"},{"key":"1419_CR90","first-page":"946","volume":"24","author":"A Watson","year":"1993","unstructured":"Watson, A. (1993). DCTune: A technique for visual optimization of DCT quantization matrices for individual images. Society for Information Display Digest of Technical Papers, 24, 946\u2013949.","journal-title":"Society for Information Display Digest of Technical Papers"},{"issue":"8","key":"1419_CR91","doi-asserted-by":"publisher","first-page":"1164","DOI":"10.1109\/83.605413","volume":"6","author":"AB Watson","year":"1997","unstructured":"Watson, A. B., Yang, G. Y., Solomon, J. A., & Villasenor, J. (1997). Visibility of wavelet quantization noise. IEEE Transactions on Image Processing, 6(8), 1164\u20131175.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR92","volume-title":"Extrapolation, interpolation and smoothing of stationary time series: with engineering applications","author":"N Wiener","year":"1950","unstructured":"Wiener, N. (1950). Extrapolation, interpolation and smoothing of stationary time series: with engineering applications. Cambridge, MA: MIT Press."},{"key":"1419_CR93","doi-asserted-by":"crossref","unstructured":"Xue, W., Mou, X., Zhang, L., & Feng, X. (2013). Perceptual fidelity aware mean squared error. In IEEE international conference on computer vision (pp. 705\u2013712).","DOI":"10.1109\/ICCV.2013.93"},{"issue":"2","key":"1419_CR94","doi-asserted-by":"publisher","first-page":"684","DOI":"10.1109\/TIP.2013.2293423","volume":"23","author":"W Xue","year":"2014","unstructured":"Xue, W., Zhang, L., Mou, X., & Bovik, A. C. (2014). Gradient magnitude similarity deviation: A highly efficient perceptual image quality index. IEEE Transactions on Image Processing, 23(2), 684\u2013695.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR95","doi-asserted-by":"crossref","unstructured":"Yang, C. Y., & Yang, M. H. (2013). Fast direct super-resolution by simple functions. In IEEE international conference on computer vision (pp. 561\u2013568).","DOI":"10.1109\/ICCV.2013.75"},{"issue":"11","key":"1419_CR96","doi-asserted-by":"publisher","first-page":"2861","DOI":"10.1109\/TIP.2010.2050625","volume":"19","author":"J Yang","year":"2010","unstructured":"Yang, J., Wright, J., Huang, T. S., & Ma, Y. (2010). Image super-resolution via sparse representation. IEEE Transactions on Image Processing, 19(11), 2861\u20132873.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR97","doi-asserted-by":"crossref","unstructured":"Ye, P., Kumar, J., & Doermann, D. (2014). Beyond human opinion scores: Blind image quality assessment based on synthetic scores. In IEEE conference on computer vision and pattern recognition (pp. 4241\u20134248).","DOI":"10.1109\/CVPR.2014.540"},{"issue":"7","key":"1419_CR98","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","volume":"26","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Zuo, W., Chen, Y., Meng, D., & Zhang, L. (2017). Beyond a Gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE Transactions on Image Processing, 26(7), 3142\u20133155.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"10","key":"1419_CR99","doi-asserted-by":"publisher","first-page":"4270","DOI":"10.1109\/TIP.2014.2346028","volume":"23","author":"L Zhang","year":"2014","unstructured":"Zhang, L., Shen, Y., & Li, H. (2014). VSI: A visual saliency-induced index for perceptual image quality assessment. IEEE Transactions on Image Processing, 23(10), 4270\u20134281.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"8","key":"1419_CR100","doi-asserted-by":"publisher","first-page":"2378","DOI":"10.1109\/TIP.2011.2109730","volume":"20","author":"L Zhang","year":"2011","unstructured":"Zhang, L., Zhang, L., Mou, X., & Zhang, D. (2011). FSIM: A feature similarity index for image quality assessment. IEEE Transactions on Image Processing, 20(8), 2378\u20132386.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1419_CR101","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A. A., Shechtman, E., & Wang, O. (2018). The unreasonable effectiveness of deep features as a perceptual metric. In IEEE conference on computer vision and pattern recognition (pp. 586\u2013595).","DOI":"10.1109\/CVPR.2018.00068"},{"key":"1419_CR102","doi-asserted-by":"crossref","unstructured":"Zhang, W., Liu, Y., Dong, C., & Qiao, Y. (2019a). RankSRGAN: Generative adversarial networks with ranker for image super-resolution. In IEEE conference on computer vision and pattern recognition (pp. 3096\u20133105).","DOI":"10.1109\/ICCV.2019.00319"},{"key":"1419_CR103","doi-asserted-by":"crossref","unstructured":"Zhang, W., Ma, K., Zhai, G., & Yang, X. (2019b). Learning to blindly assess image quality in the laboratory and wild. CoRR arXiv:1907.00516.","DOI":"10.1109\/ICIP40778.2020.9191278"},{"issue":"4","key":"1419_CR104","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1109\/LSP.2013.2244081","volume":"20","author":"X Zhang","year":"2013","unstructured":"Zhang, X., Feng, X., Wang, W., & Xue, W. (2013). Edge strength similarity for image quality assessment. IEEE Signal Processing Letters, 20(4), 319\u2013322.","journal-title":"IEEE Signal Processing Letters"},{"issue":"1","key":"1419_CR105","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/TCI.2016.2644865","volume":"3","author":"H Zhao","year":"2016","unstructured":"Zhao, H., Gallo, O., Frosio, I., & Kautz, J. (2016). Loss functions for image restoration with neural networks. IEEE Transactions on Computational Imaging, 3(1), 47\u201357.","journal-title":"IEEE Transactions on Computational Imaging"},{"issue":"7","key":"1419_CR106","doi-asserted-by":"publisher","first-page":"3528","DOI":"10.1109\/TIP.2019.2898638","volume":"28","author":"F Zhou","year":"2019","unstructured":"Zhou, F., Yao, R., Liu, B., & Qiu, G. (2019). Visual quality assessment for super-resolved images: Database and method. IEEE Transactions on Image Processing, 28(7), 3528\u20133541.","journal-title":"IEEE Transactions on Image Processing"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-020-01419-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-020-01419-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-020-01419-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T06:40:55Z","timestamp":1744180855000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-020-01419-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,21]]},"references-count":106,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,4]]}},"alternative-id":["1419"],"URL":"https:\/\/doi.org\/10.1007\/s11263-020-01419-7","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,21]]},"assertion":[{"value":"1 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}