{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:10:25Z","timestamp":1767337825443,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,11,5]],"date-time":"2021-11-05T00:00:00Z","timestamp":1636070400000},"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":["U1704242"],"award-info":[{"award-number":["U1704242"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Affected by the uneven concentration of coal dust and low illumination, most of the images captured in the top-coal caving face have low definition, high haze and serious noise. In order to improve the visual effect of underground images captured in the top-coal caving face, a novel single-channel Retinex dedusting algorithm with frequency domain prior information is proposed to solve the problem that Retinex defogging algorithm cannot effectively defog and denoise, simultaneously, while preserving image details. Our work is inspired by the simple and intuitive observation that the low frequency component of dust-free image will be amplified in the symmetrical spectrum after adding dusts. A single-channel multiscale Retinex algorithm with color restoration (MSRCR) in YIQ space is proposed to restore the foggy approximate component in wavelet domain. After that the multiscale convolution enhancement and fast non-local means (FNLM) filter are used to minimize noise of detail components while retaining sufficient details. Finally, a dust-free image is reconstructed to the spatial domain and the color is restored by white balance. By comparing with the state-of-the-art image dedusting and defogging algorithms, the experimental results have shown that the proposed algorithm has higher contrast and visibility in both subjective and objective analysis while retaining sufficient details.<\/jats:p>","DOI":"10.3390\/sym13112097","type":"journal-article","created":{"date-parts":[[2021,11,7]],"date-time":"2021-11-07T20:42:54Z","timestamp":1636317774000},"page":"2097","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Joint Dedusting and Enhancement of Top-Coal Caving Face via Single-Channel Retinex-Based Method with Frequency Domain Prior Information"],"prefix":"10.3390","volume":"13","author":[{"given":"Chengcai","family":"Fu","sequence":"first","affiliation":[{"name":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengli","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoxiao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoying","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wu, D., and Zhang, S. (2018, January 28\u201331). Research on image enhancement algorithm of coal mine dust. Proceedings of the 2018 International Conference on Sensor Networks and Signal Processing (SNSP), Xian, China.","DOI":"10.1109\/SNSP.2018.00057"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"122459","DOI":"10.1109\/ACCESS.2019.2934981","article-title":"Retinex-based laplacian pyramid method for image defogging","volume":"7","author":"Zhou","year":"2019","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"72492","DOI":"10.1109\/ACCESS.2019.2920403","article-title":"Single image defogging based on multi-channel convolutional MSRCR","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_4","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_5","doi-asserted-by":"crossref","first-page":"5641","DOI":"10.1109\/ACCESS.2018.2794340","article-title":"A fast single-image dehazing method based on a physical model and gray projection","volume":"6","author":"Wang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_6","first-page":"1","article-title":"Gray-scale image dehazing guided by scene depth information","volume":"2016","author":"Jiang","year":"2016","journal-title":"Math. Probl. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1109\/TMM.2018.2871955","article-title":"An iterative image dehazing method with polarization","volume":"21","author":"Shen","year":"2019","journal-title":"IEEE Trans. Multimedia"},{"key":"ref_8","unstructured":"Schechner, Y., Narasimhan, S., and Nayar, S. (2001, January 8\u201314). Instant dehazing of images using polarization. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, Kauai, HI, USA."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3522","DOI":"10.1109\/TIP.2015.2446191","article-title":"A fast single image haze removal algorithm using color attenuation prior","volume":"24","author":"Zhu","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3104","DOI":"10.1109\/TIP.2019.2957852","article-title":"IDGCP: Image dehazing based on gamma correction prior","volume":"29","author":"Ju","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Berman, D., Treibitz, T., and Avidan, S. (July, January 26). Non-local image dehazing. Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.185"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhang, H., and Patel, V.M. (2018, January 18\u201322). Densely connected pyramid dehazing network. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00337"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1007\/s11263-019-01235-8","article-title":"Single image dehazing via multi-scale convolutional neural networks with holistic edges","volume":"128","author":"Ren","year":"2020","journal-title":"Int. J. Comput. Vis."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ren, W., Ma, L., Zhang, J., Pan, J., Cao, X., Liu, W., and Yang, M.-H. (2018, January 18\u201322). Gated fusion network for single image dehazing. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00343"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Li, B., Peng, X., Wang, Z., Xu, J., and Feng, D. (2017, January 22\u201329). AOD-Net: All-in-one dehazing network. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.511"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.dsp.2016.10.013","article-title":"Image contrast enhancement using fuzzy clustering with adaptive cluster parameter and sub-histogram equalization","volume":"62","author":"Shakeri","year":"2017","journal-title":"Digit. Signal Process."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.neucom.2015.08.113","article-title":"An enhancement method for X-ray image via fuzzy noise removal and homomorphic filtering","volume":"195","author":"Xiao","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Ye, X., Wu, G., Huang, L., Fan, F., and Zhang, Y. (2018). Image enhancement for inspection of cable images based on retinex theory and fuzzy enhancement method in wavelet domain. Symmetry, 10.","DOI":"10.3390\/sym10110570"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5022","DOI":"10.1109\/TIP.2020.2974060","article-title":"STAR: A structure and texture aware retinex model","volume":"29","author":"Xu","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Si, L., Wang, Z., Xu, R., Tan, C., Liu, X., and Xu, J. (2017). Image enhancement for surveillance video of coal mining face based on single-scale retinex algorithm combined with bilateral filtering. Symmetry, 9.","DOI":"10.3390\/sym9060093"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Sadia, H., Azeem, F., Ullah, H., Mahmood, Z., Khattak, S., and Khan, G.Z. (2018, January 17\u201319). Color image enhancement using multiscale retinex with guided filter. Proceedings of the 2018 International Conference on Frontiers of Information Technology (FIT), Islamabad, Pakistan.","DOI":"10.1109\/FIT.2018.00022"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Galdran, A., Bria, A., Alvarez-Gila, A., Vazquez-Corral, J., and Bertalmio, M. (2018, January 18\u201322). On the duality between retinex and image dehazing. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00857"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2014\/362716","article-title":"A new method of image denoising for underground coal mine based on the visual characteristics","volume":"2014","author":"Hua","year":"2014","journal-title":"J. Appl. Math."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Shang, C. (2015, January 13\u201314). A novel analyzing method to coal mine image restoration. Proceedings of the 2015 Asia-Pacific Energy Equipment Engineering Research Conference, Zhuhai, China.","DOI":"10.2991\/ap3er-15.2015.67"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Yu, C., Rui, G., and Li-Jie, D. (2016, January 27\u201328). Study of image enhancement algorithms in coal mine. Proceedings of the 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), Hangzhou, China.","DOI":"10.1109\/IHMSC.2016.237"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.cviu.2017.08.002","article-title":"Efficient single image dehazing and denoising: An efficient multi-scale correlated wavelet approach","volume":"162","author":"Liu","year":"2017","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1109\/83.557356","article-title":"Properties and performance of a center\/surround retinex","volume":"6","author":"Jobson","year":"1997","journal-title":"IEEE Trans. Image Process."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Li, M., Liu, J., Yang, W., and Guo, Z. (2018). Joint denoising and enhancement for low-light images via retinex model. Digital TV and Wireless Multimedia Communication, Springer.","DOI":"10.1007\/978-981-10-8108-8_9"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ren, X., Li, M., Cheng, W.-H., and Liu, J. (2018, January 27\u201330). Joint enhancement and denoising method via sequential decomposition. Proceedings of the 2018 IEEE International Symposium on Circuits and Systems (ISCAS), Florence, Italy.","DOI":"10.1109\/ISCAS.2018.8351427"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1016\/j.ifacol.2018.08.098","article-title":"Sea cucumber image dehazing method by fusion of retinex and dark channel","volume":"51","author":"Li","year":"2018","journal-title":"IFAC PapersOnLine"},{"key":"ref_31","first-page":"1","article-title":"Dehaze enhancement algorithm based on retinex theory for aerial images combined with dark channel","volume":"07","author":"Liu","year":"2020","journal-title":"OALib"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Fu, F., and Liu, F. (2015, January 12\u201313). Wavelet-based retinex algorithm for unmanned aerial vehicle image defogging. Proceedings of the 8th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, China.","DOI":"10.1109\/ISCID.2015.308"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1166\/jmihi.2020.2859","article-title":"A medical image enhancement method based on improved multi-scale retinex algorithm","volume":"10","author":"Qin","year":"2020","journal-title":"J. Med Imaging Health Inform."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"61277","DOI":"10.1109\/ACCESS.2018.2870638","article-title":"Retinex-based perceptual contrast enhancement in images using luminance adaptation","volume":"6","author":"Fu","year":"2018","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"300","DOI":"10.5201\/ipol.2014.120","article-title":"Parameter-free fast pixelwise non-local means denoising","volume":"4","author":"Froment","year":"2014","journal-title":"Image Process. Line"},{"key":"ref_36","first-page":"1","article-title":"Structure extraction from texture via relative total variation","volume":"31","author":"Xu","year":"2012","journal-title":"ACM Trans. Graph."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/11\/2097\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:26:12Z","timestamp":1760167572000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/11\/2097"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,5]]},"references-count":36,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["sym13112097"],"URL":"https:\/\/doi.org\/10.3390\/sym13112097","relation":{},"ISSN":["2073-8994"],"issn-type":[{"type":"electronic","value":"2073-8994"}],"subject":[],"published":{"date-parts":[[2021,11,5]]}}}