{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T11:38:26Z","timestamp":1769168306065,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T00:00:00Z","timestamp":1616716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876139"],"award-info":[{"award-number":["61876139"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Fundamental Research Funds for the Central Universities","award":["XJS201201"],"award-info":[{"award-number":["XJS201201"]}]},{"name":"The Fundamental Research Funds for the Central Universities","award":["JB181206"],"award-info":[{"award-number":["JB181206"]}]},{"name":"Natural Science Basic Research Plan in Shaanxi Province of China","award":["2019JM-129"],"award-info":[{"award-number":["2019JM-129"]}]},{"name":"Natural Science Basic Research Plan in Shaanxi Province of China","award":["2021JM-136"],"award-info":[{"award-number":["2021JM-136"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Matching infrared (IR) facial probes against a gallery of visible light faces remains a challenge, especially when combined with cross-distance due to deteriorated quality of the IR data. In this paper, we study the scenario where visible light faces are acquired at a short standoff, while IR faces are long-range data. To address the issue of quality imbalance between the heterogeneous imagery, we propose to compensate it by upgrading the lower-quality IR faces. Specifically, this is realized through cascaded face enhancement that combines an existing denoising algorithm (BM3D) with a new deep-learning-based deblurring model we propose (named SVDFace). Different IR bands, short-wave infrared (SWIR) and near-infrared (NIR), as well as different standoffs, are involved in the experiments. Results show that, in all cases, our proposed approach for quality balancing yields improved recognition performance, which is especially effective when involving SWIR images at a longer standoff. Our approach outperforms another easy and straightforward downgrading approach. The cascaded face enhancement structure is also shown to be beneficial and necessary. Finally, inspired by the singular value decomposition (SVD) theory, the proposed deblurring model of SVDFace is succinct, efficient and interpretable in structure. It is proven to be advantageous over traditional deblurring algorithms as well as state-of-the-art deep-learning-based deblurring algorithms.<\/jats:p>","DOI":"10.3390\/s21072322","type":"journal-article","created":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T13:17:53Z","timestamp":1616764673000},"page":"2322","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Balancing Heterogeneous Image Quality for Improved Cross-Spectral Face Recognition"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4856-406X","authenticated-orcid":false,"given":"Zhicheng","family":"Cao","sequence":"first","affiliation":[{"name":"Molecular and Neuroimaging Engineering Research Center of Ministry of Education, School of Life Science and Technology, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4181-2518","authenticated-orcid":false,"given":"Xi","family":"Cen","sequence":"additional","affiliation":[{"name":"Molecular and Neuroimaging Engineering Research Center of Ministry of Education, School of Life Science and Technology, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0242-7609","authenticated-orcid":false,"given":"Heng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Molecular and Neuroimaging Engineering Research Center of Ministry of Education, School of Life Science and Technology, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2388-2806","authenticated-orcid":false,"given":"Liaojun","family":"Pang","sequence":"additional","affiliation":[{"name":"Molecular and Neuroimaging Engineering Research Center of Ministry of Education, School of Life Science and Technology, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1109\/TPAMI.2007.1007","article-title":"Physiology-based face recognition in the thermal infrared spectrum","volume":"29","author":"Buddharaju","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Machine Intell."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1717","DOI":"10.1109\/TIFS.2012.2213813","article-title":"Long Range Cross-Spectral Face Recognition: Matching SWIR Against Visible Light Images","volume":"7","author":"Nicolo","year":"2012","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1410","DOI":"10.1109\/TPAMI.2012.229","article-title":"Heterogeneous Face Recognition Using Kernel Prototype Similarities","volume":"35","author":"Klare","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Juefei-Xu, F., Pal, D.K., and Savvides, M. (2015, January 7\u201312). NIR-VIS Heterogeneous Face Recognition via Cross-Spectral Joint Dictionary Learning and Reconstruction. Proceedings of the The IEEE Conference on Computer Vision and Pattern Recognition Workshops, Boston, MA, USA.","DOI":"10.1109\/CVPRW.2015.7301308"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Lezama, J., Qiu, Q., and Sapiro, G. (July, January 21). Not Afraid of the Dark: NIR-VIS Face Recognition via Cross-Spectral Hallucination and Low-Rank Embedding. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.720"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hu, S., Short, N., Riggan, B.S., Chasse, M., and Sarfras, M.S. (June, January 30). Heterogeneous Face Recognition: Recent Advances in Infrared-to-Visible Matching. Proceedings of the The 12th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017), Washington, DC, USA.","DOI":"10.1109\/FG.2017.126"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Cho, S.W., Baek, N.R., Kim, M.C., Kim, J.H., and Park, K.R. (2018). Face Detection in Nighttime Images Using Visible-Light Camera Sensors with Two-Step Faster Region-Based Convolutional Neural Network. Sensors, 18.","DOI":"10.3390\/s18092995"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1007\/s11263-019-01175-3","article-title":"Synthesis of High-Quality Visible Faces from Polarimetric Thermal Faces using Generative Adversarial Networks","volume":"127","author":"Zhang","year":"2019","journal-title":"Int. J. Comput. Vis."},{"key":"ref_9","unstructured":"Di, X., Riggan, B.S., Hu, S., Short, N.J., and Patel, V.M. (2021, March 25). Polarimetric Thermal to Visible Face Verification via Self-Attention Guided Synthesis. Available online: https:\/\/arxiv.org\/abs\/1901.00889."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Le, H.A., and Kakadiaris, I.A. (2020, January 27\u201329). DBLFace: Domain-Based Labels for NIR-VIS Heterogeneous Face Recognition. Proceedings of the 2020 IEEE International Joint Conference on Biometrics (IJCB), Seoul, Korea.","DOI":"10.1109\/IJCB48548.2020.9304884"},{"key":"ref_11","unstructured":"Kirschner, J. (2015, January 04). SWIR for Target Detection, Recognition, Furthermore, Identification. Available online: http:\/\/www.photonicsonline.com\/doc.mvc\/SWIR-For-Target-Detection-Recognition-And-0002."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lemoff, B.E., Martin, R.B., Sluch, M., Kafka, K.M., Dolby, A., and Ice, R. (2014, January 5\u20139). Automated, Long-Range, Night\/Day, Active-SWIR Face Recognition System. Proceedings of the SPIE Conference on Infrared Technology and Applications XL, Baltimore, MD, USA.","DOI":"10.1117\/12.2052716"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"27297","DOI":"10.1364\/OE.20.027297","article-title":"GeSn\/Ge heterostructure short-wave infrared photodetectors on silicon","volume":"20","author":"Gassenq","year":"2012","journal-title":"Opt. Express"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"083107","DOI":"10.1117\/1.OE.55.8.083107","article-title":"Composite multilobe descriptors for cross-spectral recognition of full and partial face","volume":"55","author":"Cao","year":"2016","journal-title":"Opt. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Klare, B., and Jain, A.K. (2010, January 23\u201326). Heterogeneous Face Recognition: Matching NIR to Visible Light Images. Proceedings of the International Conference on Pattern Recognition, Istanbul, Turkey.","DOI":"10.1109\/ICPR.2010.374"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.patrec.2015.10.018","article-title":"Fusion of operators for heterogeneous periocular recognition at varying ranges","volume":"82","author":"Cao","year":"2016","journal-title":"Pattern Recognit. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1007\/s11263-016-0933-2","article-title":"Deep Perceptual Mapping for Cross-Modal Face Recognition","volume":"122","author":"Sarfraz","year":"2017","journal-title":"International Journal of Computer Vision"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.neucom.2015.11.137","article-title":"A Gabor-based Network for Heterogeneous Face Recognition","volume":"261","author":"Oh","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Iranmanesh, S.M., Dabouei, A., Kazemi, H., and Nasrabadi, N.M. (2018, January 20\u201323). Deep Cross Polarimetric Thermal-to-Visible Face Recognition. Proceedings of the 2018 International Conference on Biometrics (ICB), Gold Coast, Australia.","DOI":"10.1109\/ICB2018.2018.00034"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1109\/TPAMI.2019.2961900","article-title":"Adversarial Cross-Spectral Face Completion for NIR-VIS Face Recognition","volume":"42","author":"He","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4699","DOI":"10.1109\/TNNLS.2019.2957285","article-title":"Coupled Attribute Learning for Heterogeneous Face Recognition","volume":"31","author":"Liu","year":"2020","journal-title":"IEEE Trans. Neural Networks Learn. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Cao, Z., Schmid, N.A., and Li, X. (2016, January 18\u201319). Image Disparity in Cross-Spectral Face Recognition: Mitigating Camera and Atmospheric Effects. Proceedings of the SPIE Conference on Automatic Target Recognition XXVI, Baltimore, MD, USA.","DOI":"10.1117\/12.2225149"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1111\/1467-9280.00144","article-title":"Face recognition in poor-quality video: Evidence from security surveillance","volume":"10","author":"Burton","year":"1999","journal-title":"Psychol. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1109\/TIM.2009.2037989","article-title":"Image-quality-based adaptive face recognition","volume":"59","author":"Sellahewa","year":"2010","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3750","DOI":"10.1016\/j.patcog.2014.06.004","article-title":"Nighttime face recognition at large standoff: Cross-distance and cross-spectral matching","volume":"47","author":"Kang","year":"2014","journal-title":"Pattern Recognit."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1160","DOI":"10.1109\/TPAMI.2003.1227990","article-title":"Comparison and combination of ear and face images in appearance-based biometrics","volume":"25","author":"Chang","year":"2003","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_27","unstructured":"Fronthaler, H., Kollreider, K., and Bigun, J. (2006, January 17\u201322). Automatic image quality assessment with application in biometrics. Proceedings of the CVPRW\u201906. Conference onComputer Vision and Pattern Recognition Workshop, New York, NY, USA."},{"key":"ref_28","unstructured":"Abaza, A., Harrison, M.A., and Bourlai, T. (2012, January 11\u201315). Quality metrics for practical face recognition. Proceedings of the 2012 21st International Conference on Pattern Recognition (ICPR), Tsukuba, Japan."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1109\/TPAMI.2007.1019","article-title":"Performance of biometric quality measures","volume":"29","author":"Grother","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Nandakumar, K., Chen, Y., Jain, A.K., and Dass, S.C. (2006, January 20\u201324). Quality-based score level fusion in multibiometric systems. Proceedings of the ICPR 2006. 18th International Conference on Pattern Recognition, Hong Kong, China.","DOI":"10.1109\/ICPR.2006.951"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1109\/TPAMI.2007.70796","article-title":"Likelihood ratio-based biometric score fusion","volume":"30","author":"Nandakumar","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kryszczuk, K., and Drygajlo, A. (2007). Improving classification with class-independent quality measures: Q-stack in face verification. Advances in Biometrics, Springer.","DOI":"10.1007\/978-3-540-74549-5_117"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1049\/iet-spr.2008.0174","article-title":"Improving biometric verification with class-independent quality information","volume":"3","author":"Kryszczuk","year":"2009","journal-title":"IET Signal Process."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1364\/JOSA.62.000055","article-title":"Bayesian-Based Iterative Method of Image Restoration","volume":"62","author":"Richardson","year":"1972","journal-title":"J. Opt. Soc. Am."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s11263-014-0727-3","article-title":"Deblurring Shaken and Partially Saturated Images","volume":"110","author":"Whyte","year":"2014","journal-title":"Int. J. Comput. Vis."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2191","DOI":"10.1109\/TPAMI.2010.45","article-title":"Blind image deconvolution using machine learning for three-dimensional microscopy","volume":"32","author":"Kenig","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_37","unstructured":"Krizhevsky, A., Sutskever, I., and Hinton, G. (2012, January 3\u20136). ImageNet classification with deep convolutional neural networks. Proceedings of the International Conference on Neural Information Processing Systems, Lake Tahoe, NV, USA."},{"key":"ref_38","unstructured":"Chao, D., Chen, C.L., He, K., and Tang, X. (2014, January 6\u20137). Learning a Deep Convolutional Network for Image Super-Resolution. Proceedings of the ECCV2014, Lecture Notes in Computer Science, Zurich, Switzerland."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Sun, J., Cao, W., Xu, Z., and Ponce, J. (2015, January 7\u201312). Learning a convolutional neural network for non-uniform motion blur removal. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298677"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1439","DOI":"10.1109\/TPAMI.2015.2481418","article-title":"Learning to Deblur","volume":"38","author":"Schuler","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Nah, S., Kim, T.H., and Lee, K.M. (2017, January 21\u201326). Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.35"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., and Matas, J. (2018, January 18\u201322). DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00854"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","article-title":"Image denoising by sparse 3-D transform-domain collaborative filtering","volume":"16","author":"Dabov","year":"2007","journal-title":"IEEE Trans. Image Process."},{"key":"ref_44","unstructured":"Simonyan, K., and Zisserman, A. (2021, March 25). Very Deep Convolutional Networks for Large-Scale Image Recognition. Available online: https:\/\/arxiv.org\/abs\/1409.1556v3."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (2016, January 27\u201330). Deep Residual Learning for Image Recognition. Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Johnson, P.A., Lopez-Meyer, P., Sazonova, N., Hua, F., and Schuckers, S. (2010, January 27\u201329). Quality in face and iris research ensemble (Q-FIRE). Proceedings of the 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), Washington, DC, USA.","DOI":"10.1109\/BTAS.2010.5634513"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2354","DOI":"10.1109\/TPAMI.2011.148","article-title":"Understanding Blind Deconvolution Algorithms","volume":"33","author":"Levin","year":"2011","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"223548","DOI":"10.1109\/ACCESS.2020.3033890","article-title":"Progressive Semantic Face Deblurring","volume":"8","author":"Lee","year":"2020","journal-title":"IEEE Access"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"6251","DOI":"10.1109\/TIP.2020.2990354","article-title":"Deblurring Face Images Using Uncertainty Guided Multi-Stream Semantic Networks","volume":"29","author":"Yasarla","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Martin, R.B., Kafka, K.M., and Lemoff, B.E. (2013, January 29). Active-SWIR signatures for long-range night\/day human detection and identification. Proceedings of the SPIE Symposium on DSS, Baltimore, MD, USA.","DOI":"10.1117\/12.2016346"},{"key":"ref_51","first-page":"971","article-title":"Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns","volume":"24","author":"Ojala","year":"2002","journal-title":"IEEE Trans. Inf. For. Sec."},{"key":"ref_52","unstructured":"Guo, Y., and Xu, Z. (2008, January 8\u201311). Local Gabor phase difference pattern for face recognition. Proceedings of the International Conference on Pattern Recognition, Tampa, FL, USA."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1705","DOI":"10.1109\/TPAMI.2009.155","article-title":"WLD: A Robust Local Image Descriptor","volume":"32","author":"Chen","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. 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