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Academic Journal of Computing & Information Science, 2022, 5(14); doi: 10.25236/AJCIS.2022.051404.

Low Complexity and High Robustness Image Dehaze Algorithm

Author(s)

Changhao Ding

Corresponding Author:
Changhao Ding
Affiliation(s)

School of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, 350100, China

Abstract

This paper proposes a low complexity, high robustness dark channel prior image dehaze method. This method addresses the shortcomings of the 'dark channel prior' dehaze method by Kaiming He et al. Firstly, for the scenario of 'dark channel prior' failure, the 'linear stretching' method is proposed to estimate the dark channel after fog removal, then fuse the two 'dark channel' images, and the modified transmissivity is finally obtained. Secondly, because the introduction of the 'Guided Filter' increases the computation of the algorithm, this paper raises the 'pixel-based transmissivity estimation' proposed to remove the 'Guided filter', which not only saves hardware resources, but also eliminates the 'block effect' and 'Halo effect'. 

Keywords

Image Dehaze Algorithm, Dark Channel Prior, Low Complexity Dehaze Algorithm, High Robustness Dehaze Algorithm

Cite This Paper

Changhao Ding. Low Complexity and High Robustness Image Dehaze Algorithm. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 14: 27-32. https://doi.org/10.25236/AJCIS.2022.051404.

References

[1] Zhao, P.,  Xiong, N. N. ,  Wang, B. , &  Niu, B. . (2021). Review of single image defogging. International Journal of Sensor Networks, 35(2), 111.

[2] Andrew, A. M.. (2001). Geometric partial differential equations and image analysis. Kybernetes, 31(2).

[3] Oakley, J. P., & Satherley, B. L.. (1998). Improving image quality in poor visibility conditions using a physical model for contrast degradation. IEEE Transactions on Image Processing, 7(2), 167-179.

[4] Tan, R. T.. (2008). Visibility in bad weather from a single image. In: 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008). Anchorage, Alaska, USA. pp. 1-8

[5] He, K., Sun, J. and Tang, X. (2011). Single Image Haze Removal Using Dark Channel Prior.  In:2018 2nd International Conference on Computer Science and Intelligent Communication (CSIC 2018). Washington, DC, USA. pp. 2341-2353.

[6] Pei, T., Ma, Q., Xue, P., Ding, Y., Hao, L., & Yu, T. (2019) Nighttime Haze Removal Using Bilateral Filtering and Adaptive Dark Channel Prior. In: 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC). Xiamen, China. pp. 218-222.

[7] He, K., Sun, J. and Tang, X. (2010). Guided image filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 6, pp. 1397-1409.