{"id":8449,"date":"2026-08-03T00:08:53","date_gmt":"2026-08-02T16:08:53","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=8449"},"modified":"2026-08-22T17:20:17","modified_gmt":"2026-08-22T09:20:17","slug":"an-improved-brightness-balancing-method-and-its-gpu-acceleration-for-digital-images","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=an-improved-brightness-balancing-method-and-its-gpu-acceleration-for-digital-images","title":{"rendered":"An Improved Brightness Balancing Method and its GPU Acceleration for Digital Images"},"content":{"rendered":"\n
\n
\n

<\/i> 2016<\/a><\/p>\n<\/div>\n\n\n\n

\n

<\/i> Volume 19, Issue 4<\/a><\/p>\n<\/div>\n\n\n\n

\n
\n
\n
\n

Rui-Bin Zhao1,3<\/sup>, Yan-Ling Zhang2<\/sup><\/i><\/a>, Ming-Yong Pang1<\/sup> and Sheng-Hui Zhao2<\/sup><\/p>\n\n\n\n

1<\/sup>Department of Education Technology, Nanjing Normal University, Nanjing, P.R. China <\/p>\n\n\n\n

2<\/sup>School of Computer and Information Engineering, Chuzhou University, Chuzhou, P.R. China <\/p>\n\n\n\n

3<\/sup>Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou, P.R. China<\/p>\n<\/div>\n\n\n\n

\n

Received:\u00a0January 26, 2016
Accepted:\u00a0July 13, 2016
Publication Date:\u00a0August 03, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

An original image (a) and its subtracted image (b).<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:  BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.2016.19.4.14<\/a>  <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

<\/div>\n\n\n\n

Cloud and fog always lead to unbalance brightness in digital images, which limit information recognition and extraction. Based on an assumption that a cloud-fog covered image is an overlaying result of a normal ground image and a cloud-fog maskimage, this paper proposes an improved method for balancing brightness of digital image by removing cloud-fog effect through the following four steps: generating cloud-fog maskimage, subtracting cloud-fog maskimage, choosing reference image, and locally adaptive enhancing. Additionally, in order to avoid time-consuming for large images, a parallel solution is introduced for accelerating the method based on graphics processing unit (GPU) acceleration. Finally, the method was tested by using different cloud-fog covered images, and the experiments verify that the method is effective at balancing brightness and its efficiency can be significantly improved through central processing unit and graphics processing unit (CPU-GPU) cooperative computing.<\/p>\n\n\n\n

Keywords:\u00a0Digital Images, Brightness Balancing, Cloud-fog Removing, GPU Acceleration<\/em><\/p>\n\n\n\n

<\/div>\n\n\n\n
\n
    \n
  1. [1] Tseng, D. C., Tseng, H. T. and Chien, C. L., \u201cAutomatic Cloud Removal from Multi-temporal SPOT Images,\u201d <\/span>Applied Mathematics and Computation<\/span><\/i>, Vol. 205, No. 2, pp. 584\u2013600 (2008). doi: 10.1016\/j.amc.2008.05.050<\/span><\/li>\n
  2. [2] Cheng, Q., Shen, H., Zhang, L. and Zeng, C., \u201cCloud Removal for Remotely Sensed Images by Similar Pixel Replacement Guided wit<\/span>h a Spatio-temporal MRF Model,\u201d ISPRS Journal of Photogrammetry and Remote Sensing<\/span><\/i>, Vol. 92, No. 2, pp. 54\u201368 (2014). doi: 10.1016\/j.isprsjprs.2014.02.015<\/span><\/li>\n
  3. [3] Oakley, J. P. and Satherley, B. L., \u201cImproving Image Quality in Poor Visibility Conditions Using a Physical Model for Cont<\/span>rast Degradation,\u201d IEEE Transactions on Image Processing<\/i>, Vol. 7, No. 2, pp. 167\u2013179 (1998). doi: 10.1109\/83.660994<\/li>\n
  4. [4] Sun, W., \u201cA New Single-image Fog Removal Algorithm Based on Physical Model,\u201d Optik-International Journal for Light and Electron Optics<\/i>, Vol. 124, No. 21, pp. 4770\u20134775 (2013). doi: 10.1016\/j.ijleo.2013.01.097<\/li>\n
  5. [5] Xiao, L., Li, C., Wu, Z. and Wang, T., \u201cAn Enhancement Method for X-ray Image via Fuzzy Noise Removal and Homomorphic Filtering,\u201d <\/span>Neurocomputing<\/span><\/i>, Vol. 195, No. 24, pp. 56\u201364 (2016). doi: 10.1016\/j.neucom.2015.08.113<\/span><\/li>\n
  6. [6] Cao, B., Zhu, B., Li, R., Yang, X. and Mo, D., \u201cWallis <\/span>Algorithm for Single Image Dodging,\u201d <\/span>Journal of Geomatics Science and Techno<\/span>logy<\/span><\/i>, Vol. 29, No. 5, pp. 373\u2013377 (2012) (Chinese).<\/span><\/li>\n
  7. [7] Raju, A., Dwarakish, G. S. and Reddy, D. V., \u201cA Comparative Analysis of Histogram Equalization based Techniques for Contr<\/span>ast Enhancement and Brightness Preserving,\u201d International Journal of Signal Processing, Image Processing and Pattern Recognition<\/span><\/i>, Vol. 6, No. 5, pp. 353\u2013366 (2013). doi: 10.14257\/ijsip.2013.6.5.31<\/span><\/li>\n
  8. [8] Ancuti, C. O. and Ancuti, C., \u201cSingle Image Dehazing by <\/span>Multi-scale Fusion,\u201d <\/span>IEEE Transactions on Image Processing<\/span><\/i>, Vol. 22, No<\/span>. 8, pp. 3271\u20133282 (2013). doi: 10.1109\/TIP.2013.2262284<\/span><\/li>\n
  9. [9] Owens, J. D., Luebke, D., Govindaraju, N., et al., \u201cA Survey of General-Purpose Computation <\/span>on Graphics Hardware,\u201d <\/span>Computer G<\/span>raphics Forum<\/span><\/i>, Vol. 26, No. 1, pp. 80\u2013113 (2007). doi: 10.1111\/j.1467-8659.2007.01012.x<\/span><\/li>\n
  10. [<\/span>10] Werff, H. M. A. and Bakker, W. H., \u201cImplementation and Performance of a General Purpose Graphics Processing Unit in Hyperspe<\/span>ctral Image Analysis,\u201d <\/span>International <\/span>Journal of Applied Earth Observation and Geoinformation<\/span><\/i>, Vol. 26, No. 1, pp. 312\u201332<\/span>1 (2014). doi: 10.1016\/j.jag.2013<\/span>.08.009<\/span><\/li>\n
  11. [11] Kim, S. K. and Kim, Y. J., \u201cGPGPU-Perf: Efficient, Interval-based DVFS <\/span>Algorithm for Mobile GPGPU Applications,\u201d <\/span>Visual Compu<\/span>ter<\/span><\/i>, Vol. 31, No. 6, pp. 1045\u20131054 (2015). doi: 10.1007\/s00371-015-1111-1<\/span><\/li>\n
  12. [12] Che, S., Boyer, M., Meng, J., et al., \u201cA Performance Study of General-purpose Applications on Graphics Processors Using CUDA,\u201d <\/span>Jo<\/span>urnal of Parallel and Distributed Computing<\/i>, Vol. 68, No. 10, pp. 1370\u20131380 (2008). doi: 10.1016\/j.jpdc.2008.05.014<\/li>\n<\/ol>\n<\/div>\n\n\n\n

    <\/p>\n","protected":false},"author":3,"template":"wp-custom-template-detail-4-aricles","meta":{"_uag_custom_page_level_css":""},"categories":[1563,6,1567],"tags":[1622],"acf":[],"uagb_featured_image_src":[],"uagb_author_info":{"display_name":"\u6797\u923a\u6db5","author_link":"\/jase\/?author=3"},"uagb_comment_info":0,"uagb_excerpt":" Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited. Download Citation:  BibTeX | http:\/\/dx.doi.org\/10.6180\/jase.2016.19.4.14   Download PDF Cloud and fog always lead to unbalance brightness in digital images,…","_links":{"self":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope\/8449"}],"collection":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope"}],"about":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/types\/tkuisotope"}],"author":[{"embeddable":true,"href":"\/jase\/index.php?rest_route=\/wp\/v2\/users\/3"}],"wp:attachment":[{"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8449"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8449"},{"taxonomy":"post_tag","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8449"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}