{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T16:07:31Z","timestamp":1782835651163,"version":"3.54.5"},"reference-count":29,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,11]],"date-time":"2018-04-11T00:00:00Z","timestamp":1523404800000},"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":["61372167"],"award-info":[{"award-number":["61372167"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701524"],"award-info":[{"award-number":["61701524"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>There are many artificial parameters when fuse infrared and visible images, to overcome the lack of detail in the fusion image because of the artifacts, a novel fusion algorithm for infrared and visible images that is based on different constraints in non-subsampled shearlet transform (NSST) domain is proposed. There are high bands and low bands of images that are decomposed by the NSST. After analyzing the characters of the bands, fusing the high level bands by the gradient constraint, the fused image can obtain more details; fusing the low bands by the constraint of saliency in the images, the targets are more salient. Before the inverse NSST, the Nash equilibrium is used to update the coefficient. The fused images and the quantitative results demonstrate that our method is more effective in reserving details and highlighting the targets when compared with other state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s18041169","type":"journal-article","created":{"date-parts":[[2018,4,11]],"date-time":"2018-04-11T12:16:50Z","timestamp":1523449010000},"page":"1169","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Infrared and Visible Image Fusion Based on Different Constraints in the Non-Subsampled Shearlet Transform Domain"],"prefix":"10.3390","volume":"18","author":[{"given":"Yan","family":"Huang","sequence":"first","affiliation":[{"name":"Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi\u2019an 710038, Shaanxi, China"},{"name":"School of Management Engineering, Xi\u2019an University of Finance and Economics, Xi\u2019an 710100, Shaanxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duyan","family":"Bi","sequence":"additional","affiliation":[{"name":"Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi\u2019an 710038, Shaanxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongpeng","family":"Wu","sequence":"additional","affiliation":[{"name":"The 93575 Unit of PLA, Chengde 067000, Hebei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"0114001","DOI":"10.3788\/CJL201542.0114001","article-title":"A new adaptive fusion method based on saliency analysis for remote sensing images","volume":"42","author":"Libao","year":"2015","journal-title":"Chin. J. Lasers"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.inffus.2012.03.002","article-title":"Multi-model medical image fusion using the inter-scale and intra-scale dependencies between image shift-invariant shearlet coefficients","volume":"19","author":"Wang","year":"2014","journal-title":"Inf. Fusion"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1010002","DOI":"10.3788\/AOS201737.1010002","article-title":"Fusion of Infrared and Visible Image Based on Shearlet Transform and Neighborhood Structure Features","volume":"37","author":"Wenshan","year":"2017","journal-title":"Acta Opt. Sinica"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"061002","DOI":"10.3788\/LOP52.061002","article-title":"Study on fusion of visual and infrared images based on NSCT","volume":"52","author":"Musheng","year":"2015","journal-title":"Laser Optoelectron. Prog."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.infrared.2014.02.013","article-title":"A fusion method for visible and infrared images based on contrast pyramid with teaching learning based optimization","volume":"64","author":"Jin","year":"2014","journal-title":"Infrared Phys. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.inffus.2015.06.006","article-title":"Combining the spectral PCA and spatial PCA fusion methods by an optimal filter","volume":"27","author":"Shahdoosti","year":"2016","journal-title":"Inf. Fusion"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.infrared.2016.01.009","article-title":"Two-scale image fusion of visible and infrared images using saliency detection","volume":"76","author":"Durga","year":"2016","journal-title":"Infrared Phys. Technol."},{"key":"ref_8","first-page":"750","article-title":"An image fusion algorithm using wavelet transform","volume":"32","author":"Rui","year":"2004","journal-title":"Acta Electron. Sin."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2091","DOI":"10.1109\/TIP.2005.859376","article-title":"The contourlet transform: An efficient directional multiresolution image representation","volume":"14","author":"Do","year":"2005","journal-title":"IEEE Trans. Image Process."},{"key":"ref_10","first-page":"905","article-title":"Remote sensing image fusion method based on contourlet coefficients\u2019 correlativity of directional region","volume":"14","author":"Wang","year":"2010","journal-title":"J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"270","DOI":"10.4304\/jmm.8.3.270-276","article-title":"Multimodal medical image fusion framework based on simplified PCNN in Nonsubsampled contourlet transform domain","volume":"8","author":"Wang","year":"2013","journal-title":"J. Multimed."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.acha.2005.07.002","article-title":"Wavelets with composite dilations and their MRA properties","volume":"20","author":"Guo","year":"2006","journal-title":"Appl. Comput. Harmon. Anal."},{"key":"ref_13","unstructured":"Glenn, E., Labate, D., and Lim, W. (November, January 29). Optimally sparse image representations using Shearlets. Proceedings of the Fortieth Asilomar Conference on the Signals, Systems and Computers (ACSSC\u201906), Pacific Grove, CA, USA."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.acha.2007.09.003","article-title":"Sparse directional image representations using the discrete shearlet transform","volume":"25","author":"Glenn","year":"2008","journal-title":"Appl. Comput. Harmon. Anal."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.aeue.2015.11.004","article-title":"A novel algorithm of remote sensing image fusion based on shift-invariant shearlet transform and regional selection","volume":"70","author":"Luo","year":"2016","journal-title":"Int. J. Electron Commun."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wan, W., Yang, Y., and Lee, H.J. (2018). Practical remote sensing image fusion method based on guided filter and improved SML in the NSST domain. Signal Image and Video Processing, Springer.","DOI":"10.1007\/s11760-018-1240-x"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.inffus.2016.02.001","article-title":"Infrared and visible image fusion via gradient transfer and total variation minimization","volume":"31","author":"Ma","year":"2016","journal-title":"Inf. Fusion"},{"key":"ref_18","unstructured":"Lei, W. (2013). Study for the Key Algorithms in Multi-Modal Medical Image Registration and Fusion, South China University of Technology."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.neucom.2016.03.009","article-title":"Infrared and visible image fusion using total variation model","volume":"202","author":"Ma","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1109\/83.902288","article-title":"The digital TV filter and nonlinear denoising","volume":"10","author":"Chan","year":"2001","journal-title":"IEEE Trans. Image Process."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1254","DOI":"10.1109\/34.730558","article-title":"A Model of Saliency-Based Visual Attention for Rapid Scene Analysis","volume":"20","author":"Itti","year":"1998","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Liu, T., Sun, J., and Zheng, N.N. (2007, January 17\u201322). Learning to detect a salient object. Proceedings of the IEEE Conference on Computer Vision & Pattern Recognition, Minneapolis, MN, USA.","DOI":"10.1109\/CVPR.2007.383047"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Xie, Y.L., and Lu, H.C. (2011, January 11\u201314). Visual saliency detection based on Bayesian model. Proceedings of the IEEE International Conference on Image Processing, Brussels, Belgium.","DOI":"10.1109\/ICIP.2011.6116634"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1915","DOI":"10.1109\/TPAMI.2011.272","article-title":"Context-Aware Saliency Detection","volume":"34","author":"Goferman","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5202","DOI":"10.1016\/j.ijleo.2014.05.001","article-title":"Saliency detection based on diffusion maps","volume":"125","author":"Yang","year":"2014","journal-title":"Optik"},{"key":"ref_26","first-page":"1679","article-title":"Image saliency detection based on region merging","volume":"28","author":"Feng","year":"2016","journal-title":"J. Comput. Aided Des. Comput. Graph."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2864","DOI":"10.1109\/TIP.2013.2244222","article-title":"Image fusion with guided filtering","volume":"22","author":"Li","year":"2013","journal-title":"IEEE Trans. Image Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1109\/97.995823","article-title":"A universal image quality index","volume":"9","author":"Wang","year":"2002","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_29","unstructured":"Piella, G., and Heijmans, H. (2003, January 14\u201317). A new quality metric for image fusion. Proceedings of the Tenth International Conference on Image Processing, Barcelona, Spain."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/1169\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:00:23Z","timestamp":1760194823000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/1169"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,11]]},"references-count":29,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["s18041169"],"URL":"https:\/\/doi.org\/10.3390\/s18041169","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,4,11]]}}}