Improved partial differential equation and fast approximation algorithm for hazy/underwater/dust storm image enhancement
DOI:
https://doi.org/10.14738/aivp.73.6694Abstract
This paper presents an improved and modified partial differential equation (PDE)-based de-hazing algorithm. The proposed method combines logarithmic image processing models in a PDE formulation refined with linear filter-based operators in either spatial or frequency domain. Additionally, a fast, simplified de-hazing function approximation of the hazy image formation model is developed in combination with fuzzy homomorphic refinement. The proposed algorithm solves the problem of image darkening and over-enhancement of edges in addition to enhancement of dark image regions encountered in previous formulations. This is in addition to avoiding enhancement of sky regions in de-hazed images while avoiding halo effect. Furthermore, the proposed algorithm is utilized for underwater and dust storm image enhancement with the incorporation of a modified global contrast enhancement algorithm. Experimental comparisons indicate that the proposed approach surpasses a majority of the algorithms from the literature based on quantitative image quality metrics.
References
Sungmin Lee, Seokmin Yun, Ju-Hun Nam, Chee Sun Won, and Seung-Won Jung, A review on dark channel prior based image dehazing algorithms. EURASIP Journal on Image and Video Processing,
Dilbad Singh and Vijay Kumar, A Comprehensive Review of Computational Dehazing Techniques. Archives of Computational Methods in Engineering, pp. 1-13, September 2018.
Kaimin He, Jian Sun, and Xiaoou Tang, Single Image Haze Removal Using Dark Channel Prior. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 33, no. 12, pp. 2341-2353,
Bo Li, Shuhang Wang, Jin Zheng, and Liping Zheng, Single image haze removal using contentadaptive dark channel and post enhancement. IET Computer Vision, vol. 8, no. 2, pp. 131-140, April 3 2014.
Kaiming He, Jian Sun, and Xiaoou Tang, Guided image filtering. IEEE transactions on pattern analysis and machine intelligence, vol. 35, no. 6, pp. 1397-1409, June 2013.
Zhengguo Li and Jinghong Zheng, Single Image De-Hazing Using Globally Guided Image Filtering. IEEE Transactions on Image Processing, vol. 27, no. 1, pp. 442-450, 8 September 2017.
C. Ancuti, CO. Ancuti, T. Haber, and P. Bekaert, Enhancing underwater images and videos by fusion. IEEE Conference on Computer Vision and Pattern Recognition, Jun 16 2012, pp. 81-88.
Adrian Galdran, Javier Vazquez-Corral, David Pardo, and Marcelo Bertalmıo, Fusion-based Variational Image Dehazing. IEEE Signal Processing Letters, vol. 24, no. 2, pp. 151-155, Feb 2017.
Adrian Galdran, Artificial Multiple Exposure Image Dehazing. Signal Processing, vol. 149, pp. 135-147, August 2018.
U. A. Nnolim, Adaptive Multi-Scale Entropy Fusion De-Hazing Based on Fractional Order. Journal of Imaging, vol. 4, no. 9, p. 108, September 6 2018.
Codruta O. Ancuti, Cosmin Ancuti, Christophe De Vleeschouwer, and Philippe Bekaert, Color Balance and Fusion for Underwater Image Enhancement. IEEE Transactions on Image Processing,
Wenqi Ren et al., Single Image Dehazing via Multi-Scale Convolutional Neural Networks. European Conference on Computer Vision, Springer International Publishing, Oct. 8, 2016 , pp. 154-169.
R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd edition.: Prentice Hall, 2002.
Vicent Caselles, Jean-Michel Morel, Guillermo Sapiro, and Allen Tannenbaum, Introduction to the Special Issue on Partial Differential Equations and Geometry-Driven Diffusion in Image Processing and Analysis. IEEE Transactions on Image Processing, vol. 7, no. 3, pp. 269-273, March 1998.
U. A. Nnolim, Smoothing and enhancement algorithms for underwater images based on partial differential equations. SPIE Journal of Electronic Imaging, vol. 26, no. 2, pp. 1-21, March 22 2017.
Uche A. Nnolim, Improved partial differential equation (PDE)-based enhancement for underwater images using local-global contrast operators and fuzzy homomorphic processes. IET Image Processing, vol. 11, no. 11, pp. 1059-1067, November 2017.
U. A. Nnolim, Partial differential equation-based hazy image contrast enhancement. Computers and Electrical Engineering, vol. 72, pp. 670-681, November 2018.
U. A. Nnolim, Image de-hazing via gradient optimized adaptive forward-reverse flow-based partial differential equation. Journal of Circuits Systems and Computers, vol. 28, no. 6, pp. 1-30, July 5 2019.
U. A. Nnolim, A PDE-based log-agnostic illumination correction algorithm. University of Nigeria, Nsukka, Technical Report 2017. [Online]. http://arxiv.org/pdf/1705.04272.
Xiaole Shen, Qingquan Li, Yingjie Tan, and Linlin Shen, An Uneven Illumination Correction Algorithm for Optical Remote Sensing Images Covered with Thin Clouds. Remote Sensing, vol. 7, no. 9, pp. 11848 - 11862, September 2015.
V. Patrascu and V. Buzuloiu, Color Image Enhancement in the Framework of Logarithmic models. The 8th IEEE International Conference on Telecommunications (IEEE ICT2001), Bucharest,Romania, 2001.
Uche A. Nnolim, FPGA-Based Multiplier-Less Log-Based Hardware Architectures for Hybrid Color Image Enhancement System. International Journal of Image and Graphics, vol. 17, no. 1, pp. 1-53, January 2017.
U. A. Nnolim, An adaptive RGB colour enhancement formulation for Logarithmic Image Processing-based algorithms. Optik, vol. 154, pp. 192–215, February 2018.
S. G. Narasimhan and S. K. Nayar, Vision and the atmosphere. International Journal of Computer Vision, vol. 48, no. 3, pp. 233-254, 2002.
Raanan Fattal, Dehazing using Colour Lines. ACM Transactions on Graphics, vol. 28, no. 4, pp. 1-14, August 2009.
Rajlaxmi Chouhan, Rajib Kumar Jha, and Prabir Kumar Biswas, Enhancement of dark and lowcontrast images using dynamic stochastic resonance. IET Image Processing, vol. 7, no. 2, pp. 174-184, 2013.
Kresimir Matkovic, Laszlo Neumann, Attila Neumann, Thomas Psik, and Werner Purgathofer, Global Contrast Factor-a New Approach to Image Contrast. Proceedings of the 1st Eurographics Conference on Computational Aesthetics in Graphics, Visualization and Imaging, Girona, Spain, May 18-20, 2005, pp. 159-167.
Artyom M. Grigoryan, John Jenkinson, and Sos Agaian, Quaternion Fourier transform based alpha-rooting method for color image measurement and enhancement. Signal Processing, April
Sabine Susstrunk and David Hasler, Measuring Colourfulness in Natural Images. IS&T/SPIE Electronic Imaging 2003: Human Vision and Electronic Imaging VIII, 2003, pp. vol. 5007, pp. 87-
Lark Kwon Choi, Jaehee You, and Alan Conrad Bovik, Referenceless Prediction of Perceptual Fog Density and Perceptual Image Defogging. IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3888-3901, November 2015.
Qingsong Zhu, Jiaming Mai, and Ling Shao, A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior. IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3522-3533, November 2015.
Z. G. Li and J. H. Zheng, Edge-preserving decomposition based single image haze removal. IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5432-5441, December 2015.
R. T. Tan, Visibility in bad weather from a single image. IEEE Conference on Computer Vision and Pattern Recognition, 2008, pp. 1-8.
Raanan Fattal, Single Image Dehazing. ACM Transactions on Graphics, vol. 72, no. 3, pp. 1-9, 2008.
J. Kopf et al., Deep photo: Model-based photograph enhancement and viewing. ACM SIGGRAPH Asia 2008 Papers, New York, NY, USA , 2008, pp. 1-10.
J.P. Tarel and N. Hautiere, Fast visibility restoration from a single color or gray level image. IEEE 12th International Conference on Computer Vision, Sep 2009, pp. 2201-2208.
C. O. Ancuti and C. Ancuti, Single image dehazing by multi-scale fusion. IEEE Transactions on Image Processing, vol. 22, no. 8, pp. 3271–3282, August 2013.
Amjad Khan, Syed Saad Azhar Ali, Atif Anwer, Syed Hasan Adil, and Fabrice Mériaudeau, Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images. IEEE Access, vol. 6, pp. 40585-40601 , 13 July 2018.
A. Galdran, D. Pardo, A. Picón, and A. Alvarez-Gila, Automatic red-channel underwater image restoration. Journal of Visual Communication and Image Representation, vol. 26, pp. 132-145, Jan 31 2015.
P. Drews-Jr et al., Transmission estimation in underwater single images. IEEE International Conference on Computer Vision Workshop, 2013, pp. 825–830.
S. Emberton, L. Chittka, and A. Cavallaro, Hierarchical rank-based veiling light estimation for underwater dehazing. British Machine Vision Conference, 1–12, 2015.
Miao Yang and Arcot Sowmya, An Underwater Color Image Quality Evaluation Metric. IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 6062-6071, December 2015.
Zohair Al-Ameen, Visibility Enhancement for Images Captured in Dusty Weather via Tuned Trithreshold Fuzzy Intensification Operators. International Journal of Intelligent Systems and Applications, vol. 8, pp. 10-17, 2016.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 Advances in Image and Video Processing
This work is licensed under a Creative Commons Attribution 4.0 International License.
