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Visibility dehazing based on channel-weighted analysis and illumination tuning

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Abstract

The air pollution and foggy weather often result in serious distortion while taking photos or recognizing patterns. He et al. have introduced the dark channel prior to solve this dehazing problem. Unfortunately, it cannot function well once the color difference of target image is large. More precisely, the dehazed result looks unnatural. Thus, we aim to develop a brand-new visibility dehazing technique based on the channel-weighted analysis and illumination tuning. The channel-weighted analysis is adopted to eliminate the unnatural effect, while the illumination tuning is applied to refine the details. Simulation results have demonstrated that the new method can guarantee the readability of a hazed image after removing noise, including the foggy photo and sandstorm one.

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References

  1. Berman D, Treibitz T, Avidan S (2016) Non-local image dehazing, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1674–1682

  2. Berman D, Treibitz T, Avidan S (2017) Air-light estimation using haze-lines, Proceedings of IEEE Conference on Computational Photography (ICCP), pp.1–9, May

  3. He KM, Sun J, Tang X (2011) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 33(12):2341–2353

    Article  Google Scholar 

  4. Huang SC, Chen BH, Wang WJ (2014) Visibility restoration of single hazy images captured in real-world weather. IEEE Transactions on Circuits and System for Video Technology 24(10):1814–1824

    Article  Google Scholar 

  5. Huang Y, Yao H, Zhao S, Zhang Y (2017) Towards more efficient and flexible face image deblurring using robust salient face landmark detection. Multimedia Tools and Applications 76(1):123–142

    Article  Google Scholar 

  6. Jegou H, Douze M, Schmid C (2008) Hamming embedding and weak geometric consistency for large scale image search, Proceedings of 10th European Conference on Computer, pp. 304–317

  7. Jian M, Dong J, Lam KM (2013) FSAM: a fast self-adaptive method for correcting non-uniform illumination for 3D reconstruction. Comput Ind 64(9):1229–1236

    Article  Google Scholar 

  8. Jian M, Lam KM, Dong J (2014) Illumination-insensitive texture discrimination based on illumination compensation and enhancement. Comput Ind 269:60–72

    MathSciNet  Google Scholar 

  9. Jian M, Yin Y, Dong J, Zhang W (2018) Comprehensive assessment of non-uniform illumination for 3D heightmap reconstruction in outdoor environments. Comput Ind 99:110–118

    Article  Google Scholar 

  10. Jiang X, Yao H, Zhao S (2017) Text image deblurring via two-tone prior. Neurocomputing 242:1–14

    Article  Google Scholar 

  11. Kopf J, Neubert B, Chen B, Cohen M, Or DC, Deussen O, Uyttendaele M, Lischinski D (2008) Deep photo: Model-based photograph enhancement and viewing, ACM Transactions on Graphics (TOG), 27(5), Article 116

  12. Meng GF, Wang Y, Duan J, Xiang S, and Pan C (2013) Efficient image dehazing with boundary constraint and contextual regularization, Proceedings of IEEE International Conference on Computer Vision (ICCV), pp. 617–624

  13. Narasimhan SG, Nayar SK (2001) Removing weather effects from monochrome images. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2:186–193

    Google Scholar 

  14. Narasimhan SG, Nayar SK (2003) Interactive (De) weathering of an image using physical models, IEEE Workshop on Color and Photometric Methods in Computer Vision (ICCV), pp. 1387–1394

  15. Narasimhan SG, Nayar SK (2003) Contrast restoration of weather degraded images. IEEE Trans Pattern Anal Mach Intell 25(6):713–724

    Article  Google Scholar 

  16. Schechner YY, Narasimhan SG, Nayar SK (2003) Polarization based vision through haze. Appl Opt 42(3):511–525

    Article  Google Scholar 

  17. Tan R (2008) Visibility in bad weather from a single image, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–8

  18. Tan K, Oakley JP (2000) Enhancement of color images in poor visibility conditions. Proceedings of IEEE International Conference on Signal Processing (ICIP) 2:788–791

    Google Scholar 

  19. Zhu M, He B, Wu Q (2018) Single image dehazing based on dark channel prior and energy minimization. IEEE Signal Processing Letters 25(2):174–178

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Information Engineering and Computer Science, Feng Chia University, 100 Wenhwa Rd., Seatwen, Taichung, 40724, Taiwan

    Jung-San Lee, Chih-Hsuan Li & Hsin-Yu Lee

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  1. Jung-San Lee
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  2. Chih-Hsuan Li
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  3. Hsin-Yu Lee
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Correspondence to Jung-San Lee.

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Lee, JS., Li, CH. & Lee, HY. Visibility dehazing based on channel-weighted analysis and illumination tuning. Multimed Tools Appl 78, 1831–1856 (2019). https://doi.org/10.1007/s11042-018-6280-2

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  • DOI: https://doi.org/10.1007/s11042-018-6280-2

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