{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:50:13Z","timestamp":1776181813215,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,1,5]],"date-time":"2022-01-05T00:00:00Z","timestamp":1641340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["No. U1803261"],"award-info":[{"award-number":["No. U1803261"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Compared with single-band remote sensing images, multispectral images can obtain information on the same target in different bands. By combining the characteristics of each band, we can obtain clearer enhanced images; therefore, we propose a multispectral image enhancement method based on the improved dark channel prior (IDCP) and bilateral fractional differential (BFD) model to make full use of the multiband information. First, the original multispectral image is inverted to meet the prior conditions of dark channel theory. Second, according to the characteristics of multiple bands, the dark channel algorithm is improved. The RGB channels are extended to multiple channels, and the spatial domain fractional differential mask is used to optimize the transmittance estimation to make it more consistent with the dark channel hypothesis. Then, we propose a bilateral fractional differentiation algorithm that enhances the edge details of an image through the fractional differential in the spatial domain and intensity domain. Finally, we implement the inversion operation to obtain the final enhanced image. We apply the proposed IDCP_BFD method to a multispectral dataset and conduct sufficient experiments. The experimental results show the superiority of the proposed method over relative comparison methods.<\/jats:p>","DOI":"10.3390\/rs14010233","type":"journal-article","created":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T23:08:26Z","timestamp":1641769706000},"page":"233","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model"],"prefix":"10.3390","volume":"14","author":[{"given":"Weijie","family":"Chen","sequence":"first","affiliation":[{"name":"The Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"}]},{"given":"Zhenhong","family":"Jia","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"}]},{"given":"Jie","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200400, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4433-7521","authenticated-orcid":false,"given":"Nikola K.","family":"Kasabov","sequence":"additional","affiliation":[{"name":"Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1020, New Zealand"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2301","DOI":"10.1109\/LGRS.2015.2473164","article-title":"Remote Sensing Image Enhancement Using Regularized-Histogram Equalization and DCT","volume":"12","author":"Fu","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1109\/TCYB.2013.2286496","article-title":"Multiresolution Imaging","volume":"44","author":"Lu","year":"2014","journal-title":"IEEE Trans. Cybern."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4009","DOI":"10.1109\/TGRS.2012.2226730","article-title":"Graph-Regularized Low-Rank Representation for Destriping of Hyperspectral Images","volume":"51","author":"Lu","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wang, J., Yang, Y., Chen, Y., and Han, Y. (2021). LighterGAN: An Illumination Enhancement Method for Urban UAV Imagery. Remote Sens., 13.","DOI":"10.3390\/rs13071371"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1016\/j.ijleo.2016.11.172","article-title":"Satellite multispectral image compression based on removing sub-bands","volume":"131","author":"Hagag","year":"2017","journal-title":"Optik"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1109\/LGRS.2012.2208616","article-title":"Satellite Image Resolution Enhancement Using Dual-Tree Complex Wavelet Transform and Nonlocal Means","volume":"10","author":"Iqbal","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/LGRS.2012.2192412","article-title":"Contrast Enhancement Using Dominant Brightness Level Analysis and Adaptive Intensity Transformation for Remote Sensing Images","volume":"10","author":"Lee","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Pyka, K. (2017). Wavelet-Based Local Contrast Enhancement for Satellite, Aerial and Close Range Images. Remote Sens., 9.","DOI":"10.3390\/rs9010025"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"7044","DOI":"10.1109\/TGRS.2016.2594339","article-title":"An Inquiry on Contrast Enhancement Methods for Satellite Images","volume":"54","author":"Lisani","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1715","DOI":"10.1109\/LGRS.2017.2730247","article-title":"An Efficient Contrast Enhancement Method for Remote Sensing Images","volume":"14","author":"Liu","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Liu, C., Sui, X., Kuang, X., Liu, Y., Gu, G., and Chen, Q. (2019). Optimized Contrast Enhancement for Infrared Images Based on Global and Local Histogram Specification. Remote Sens., 11.","DOI":"10.3390\/rs11070849"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1109\/JSTARS.2020.2975044","article-title":"A Retinex-Based Variational Model for Enhancement and Restoration of Low-Contrast Remote-Sensed Images Corrupted by Shot Noise","volume":"13","author":"Febin","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1109\/LGRS.2011.2146227","article-title":"Enhancement of Optical Remote Sensing Images by Subband-Decomposed Multiscale Retinex With Hybrid Intensity Transfer Function","volume":"8","author":"Jang","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ye, X., Yang, H., Li, C., Jia, Y., and Li, P. (2019). A Gray Scale Correction Method for Side-Scan Sonar Images Based on Retinex. Remote Sens., 11.","DOI":"10.3390\/rs11111281"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Song, M., Qu, H., Zhang, G., Tao, S., and Jin, G. (2018). A Variational Model for Sea Image Enhancement. Remote Sens., 10.","DOI":"10.3390\/rs10081313"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1538","DOI":"10.1109\/JSTARS.2012.2199085","article-title":"Semi-Automated Road Detection From High Resolution Satellite Images by Directional Morphological Enhancement and Segmentation Techniques","volume":"5","author":"Chaudhuri","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1007\/s10208-016-9341-9","article-title":"Random Laplacian Matrices and Convex Relaxations","volume":"18","author":"Bandeira","year":"2015","journal-title":"Found. Comput. Math."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1854005","DOI":"10.1142\/S0218001418540058","article-title":"The Adaptive Fractional Order Differential Model for Image Enhancement Based on Segmentation","volume":"32","author":"Chen","year":"2018","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1109\/TIP.2009.2035980","article-title":"Fractional Differential Mask: A Fractional Differential-Based Approach for Multiscale Texture Enhancement","volume":"19","author":"Pu","year":"2010","journal-title":"IEEE Trans. Image Processing"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1689","DOI":"10.1016\/j.asej.2016.12.003","article-title":"G-L fractional differential operator modified using auto-correlation function: Texture enhancement in images","volume":"9","author":"Hemalatha","year":"2018","journal-title":"Ain Shams Eng. J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"25379","DOI":"10.1007\/s11042-020-09177-x","article-title":"Enhancement of MRI images of brain tumor using Gr\u00fcnwald Letnikov fractional differential mask","volume":"79","author":"Wadhwa","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1109\/TPAMI.2010.168","article-title":"Single Image Haze Removal Using Dark Channel Prior","volume":"33","author":"He","year":"2011","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_23","unstructured":"Xuan, D., Guan, W., Yi, P., Weixin, L., Jiangtao, W., Wei, M., and Yao, L. (2011, January 11\u201315). Fast efficient algorithm for enhancement of low lighting video. Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, Barcelona, Spain."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Caballero, R., and Berbey-Alvarez, A. (2019, January 9\u201311). Underwater Image Enhancement Using Dark Channel Prior and Image Opacity. Proceedings of the 2019 7th International Engineering, Sciences and Technology Conference (IESTEC), Panama City, Panama.","DOI":"10.1109\/IESTEC46403.2019.00105"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Im, J., Yoon, I., Hayes, M.H., and Paik, J. (2013, January 26\u201331). Dark channel prior-based spatially adaptive contrast enhancement for back lighting compensation. Proceedings of the 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, BC, Canada.","DOI":"10.1109\/ICASSP.2013.6638098"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Sonkar, P.K., and Raj, K. (2020, January 6\u20138). Single Image Dehazing Using Dark Channel Prior With Median Filter and Contrast Enhancement. Proceedings of the 2020 IEEE International Conference for Innovation in Technology (INOCON), Bangluru, India.","DOI":"10.1109\/INOCON50539.2020.9298408"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Yang, H., Chen, P., Huang, C., Zhuang, Y., and Shiau, Y. (2011, January 16\u201318). Low Complexity Underwater Image Enhancement Based on Dark Channel Prior. Proceedings of the 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications, Shenzhen, China.","DOI":"10.1109\/IBICA.2011.9"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Yang, H., and Wang, J. (2010, January 16\u201318). Color image contrast enhancement by co-occurrence histogram equalization and dark channel prior. Proceedings of the 2010 3rd International Congress on Image and Signal Processing, Yantai, China.","DOI":"10.1109\/CISP.2010.5647226"},{"key":"ref_29","unstructured":"Wei, C., Wang, W., Yang, W., and Liu, J. (2018). Deep Retinex Decomposition for Low-Light Enhancement. arXiv."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Tian, L., Du, Q., Younan, N., and Kopriva, I. (2016, January 10\u201315). Multispectral image enhancement with extended offset-sparsity decomposition. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7730142"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Bhandari, A.K., Gadde, M., Kumar, A., and Singh, G.K. (2012, January 14\u201315). Comparative analysis of different wavelet filters for low contrast and brightness enhancement of multispectral remote sensing images. Proceedings of the 2012 International Conference on Machine Vision and Image Processing (MVIP), Coimbatore, India.","DOI":"10.1109\/MVIP.2012.6428766"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Bhandari, A.K., Kumar, A., and Singh, G.K. (2012, January 23\u201325). SVD Based Poor Contrast Improvement of Blurred Multispectral Remote Sensing Satellite Images. Proceedings of the 2012 Third International Conference on Computer and Communication Technology, Allahabad, India.","DOI":"10.1109\/ICCCT.2012.81"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Suresh, S., Das, D., and Lal, S. (2017, January 14\u201316). A Framework for Quality Enhancement of Multispectral Remote Sensing Images. Proceedings of the 2017 Ninth International Conference on Advanced Computing (ICoAC), Chennai, India.","DOI":"10.1109\/ICoAC.2017.8441181"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, M., Zheng, X., and Feng, C. (2013, January 21\u201326). Color constancy enhancement for multi-spectral remote sensing images. Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium\u2014IGARSS, Melbourne, VIC, Australia.","DOI":"10.1109\/IGARSS.2013.6721296"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1631\/jzus.A1000282","article-title":"Multi-spectral remote sensing image enhancement method based on PCA and IHS transformations","volume":"12","author":"Lu","year":"2011","journal-title":"J. Zhejiang Univ. SCIENCE A"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.compeleceng.2019.01.005","article-title":"Cloud enhancement of NOAA multispectral images by using independent component analysis and principal component analysis for sustainable systems","volume":"74","author":"Venkatakrishnamoorthy","year":"2019","journal-title":"Comput. Electr. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Mulla, A., Baviskar, J., Mohhamed, R., and Baviskar, A. (2015, January 8\u201310). Adaptive Band Specific Image Enhancement Scheme for Segmented Satellite Images. Proceedings of the 2015 International Conference on Pervasive Computing (ICPC), Pune, India.","DOI":"10.1109\/PERVASIVE.2015.7087163"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3937","DOI":"10.1109\/TGRS.2008.2001386","article-title":"A Fuzzy-Statistics-Based Principal Component Analysis (FS-PCA) Method for Multispectral Image Enhancement and Display","volume":"46","author":"Yang","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/MIE.2007.901479","article-title":"Fractional calculus: A mathematical tool from the past for present engineers [Past and present]","volume":"1","author":"Cafagna","year":"2007","journal-title":"IEEE Ind. Electron. Mag."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1615\/CritRevBiomedEng.2018028368","article-title":"The Concepts and Applications of Fractional Order Differential Calculus in Modelling of Viscoelastic Systems: A primer","volume":"47","author":"Matlob","year":"2017","journal-title":"Crit. Rev. Biomed. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Che, J., Shi, Y., Xiang, Y., and Ma, Y. (2012, January 16\u201318). The fractional differential enhancement of image texture features and its parallel processing optimization. Proceedings of the 2012 5th International Congress on Image and Signal Processing, Chongqing, China.","DOI":"10.1109\/CISP.2012.6470034"},{"key":"ref_42","unstructured":"Heckbert, P.S. (1994). Contrast Limited Adaptive Histogram Equalization. Graphics Gems, Academic Press."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1109\/TIP.2016.2639450","article-title":"LIME: Low-Light Image Enhancement via Illumination Map Estimation","volume":"26","author":"Guo","year":"2017","journal-title":"IEEE Trans. Image Processing"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"3665","DOI":"10.1109\/JSTARS.2017.2699200","article-title":"A Novel Adaptive Cuckoo Search Algorithm for Contrast Enhancement of Satellite Images","volume":"10","author":"Suresh","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1007\/s00607-019-00737-0","article-title":"Comparative analysis on landsat image enhancement using fractional and integral differential operators","volume":"102","author":"Luo","year":"2020","journal-title":"Computing"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1109\/LGRS.2009.2034873","article-title":"Satellite Image Contrast Enhancement Using Discrete Wavelet Transform and Singular Value Decomposition","volume":"7","author":"Demirel","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/233\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:26:49Z","timestamp":1760362009000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/233"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,5]]},"references-count":46,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14010233"],"URL":"https:\/\/doi.org\/10.3390\/rs14010233","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,5]]}}}