×

Hardy variation framework for restoration of weather degraded images. (English) Zbl 1395.94036

Summary: Images captured in fog conditions often suffer from weather of poor visibility which fades the colors and reduces the contrast in the scene. This paper proposes a novel regularization method which utilizes space transformation in order to restore the hidden scene with high dynamic range and enhanced edge information. In order to efficiently improve the visualization, the proposed method is built upon contrast stretching which can obtain better estimation map as well as solve the problem. Using minimum energy constraints, the algorithm recovers scene albedo on a number of haze images. Experimental results show that the method effectively achieves accurate and true representation.

MSC:

94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Gibson, K. B.; Võ, D. T.; Nguyen, T. Q., An investigation of dehazing effects on image and video coding, IEEE Transactions on Image Processing, 21, 2, 662-673, (2012) · Zbl 1372.94091 · doi:10.1109/tip.2011.2166968
[2] Chen, Z.; Abidi, B. R.; Page, D. L.; Abidi, M. A., Gray-level grouping (GLG): an automatic method for optimized image contrast enhancement—Part II: the variations, IEEE Transactions on Image Processing, 15, 8, 2303-2314, (2006) · doi:10.1109/tip.2006.875201
[3] Shehata, M. S.; Cai, J.; Badawy, W. M.; Burr, T. W.; Pervez, M. S.; Johannesson, R. J.; Radmanesh, A., Video-based automatic incident detection for smart roads: the outdoor environmental challenges regarding false alarms, IEEE Transactions on Intelligent Transportation Systems, 9, 2, 349-360, (2008) · doi:10.1109/tits.2008.915644
[4] Oakley, J. P.; Satherley, B. L., Improving image quality in poor visibility conditions using a physical model for contrast degradation, IEEE Transactions on Image Processing, 7, 2, 167-179, (1998) · doi:10.1109/83.660994
[5] McCartney, E. J., Optics of the Atmosphere: Scattering by Molecules and Particles, (1976), New York, NY, USA: John Wiley and Sons, New York, NY, USA
[6] Preetham, A. J.; Shirley, P.; Smits, B. E., A practical analytical model for daylight, Proceedings of Siggraph
[7] McCartney, E. J., Optics of the Atmo-Sphere: Scattering by Molecules and Particles, (1976), New York, NY, USA: John Wiley and Sons, New York, NY, USA
[8] Narasimhan, S. G.; Nayar, S. K., Contrast restoration of weather degraded images, IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, 6, 713-724, (2003) · doi:10.1109/tpami.2003.1201821
[9] Namer, E.; Shwartz, S.; Schechner, Y. Y., Skyless polarimetric calibration and visibility enhancement, Optics Express, 17, 2, 472-493, (2009) · doi:10.1364/oe.17.000472
[10] Schechner, Y. Y.; Narasimhan, S. G.; Nayar, S. K., Polarization-based vision through haze, Applied Optics, 42, 3, 511-525, (2003) · doi:10.1364/ao.42.000511
[11] Tan, R. T., Visibility in bad weather from a single image, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587643
[12] Fattal, R., Single image dehazing, ACM Transactions on Graphics, 27, 3, article 72, (2008) · doi:10.1145/1360612.1360671
[13] He, K.; Sun, J.; Tang, X., Single image haze removal using dark channel prior, IEEE Transactions on Pattern Analysis and Machine Intelligence, 33, 12, 2341-2353, (2011) · doi:10.1109/tpami.2010.168
[14] He, K.; Sun, J.; Tang, X., Guided image filtering, Proceedings of the European Conference on Computer Vision
[15] Yeh, C.-H.; Kang, L.-W.; Lee, M.-S.; Lin, C.-Y., Haze effect removal from image via haze density estimation in optical model, Optics Express, 21, 22, 27127-27141, (2013) · doi:10.1364/oe.21.027127
[16] Gibson, K.; Võ, D.; Nguyen, T., An investigation in dehazing compressed images and video, Proceedings of the IEEE OCEANS Conference, IEEE · doi:10.1109/oceans.2010.5664479
[17] Kil, T. H.; Lee, S. W.; Cho, N. I., A dehazing algorithm using dark channel prior and contrast enhancement, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP ’13), IEEE · doi:10.1109/ICASSP.2013.6638102
[18] Nishino, K.; Kratz, L.; Lombardi, S., Bayesian defogging, International Journal of Computer Vision, 98, 3, 263-278, (2012) · doi:10.1007/s11263-011-0508-1
[19] Caraffa, L.; Tarel, J.-P., Markov random field model for single image defogging, Proceedings of the IEEE Intelligent Vehicles Symposium (IV ’13) · doi:10.1109/ivs.2013.6629596
[20] Liu, X.; Zeng, F.; Huang, Z.; Ji, Y., Single color image dehazing based on digital total variation filter with color transfer, Proceedings of the 20th IEEE International Conference on Image Processing (ICIP ’13), IEEE · doi:10.1109/ICIP.2013.6738188
[21] Li, L.; Feng, W.; Zhang, J., Contrast enhancement based single image dehazing via TV-L minimization, Proceedings of the IEEE International Conference on Multimedia & Expo
[22] Tarel, J.-P.; Hautière, N.; Caraffa, L.; Cord, A.; Halmaoui, H.; Gruyer, D., Vision enhancement in homogeneous and heterogeneous fog, IEEE Intelligent Transportation Systems Magazine, 4, 2, 6-20, (2012) · doi:10.1109/mits.2012.2189969
[23] Bertero, M.; Poggio, T.; Torre, V., Ill-posed problems in early vision, Proceedings of the Royal Society B: Biological Sciences, 226, 1244, 303-323, (1985) · Zbl 0587.65085
[24] Cucker, F.; Smale, S., Best choices for regularization parameters in learning theory: on the bias-variance problem, Foundations of Computational Mathematics, 2, 4, 413-428, (2002) · Zbl 1057.68085 · doi:10.1007/s102080010030
[25] Rudin, L. I.; Osher, S.; Fatemi, E., Nonlinear total variation based noise removal algorithms, Physica D: Nonlinear Phenomena, 60, 1–4, 259-268, (1992) · Zbl 0780.49028 · doi:10.1016/0167-2789(92)90242-f
[26] Babacan, S. D.; Molina, R.; Katsaggelos, A. K., Parameter estimation in TV image restoration using variational distribution approximation, IEEE Transactions on Image Processing, 17, 3, 326-339, (2008) · doi:10.1109/tip.2007.916051
[27] Huang, L.; Xiao, L.; Wei, Z.; Zhang, Z., Variational image restoration based on Poisson singular integral and curvelet-type decomposition space regularization, Proceedings of the 18th IEEE International Conference on Image Processing
[28] Deng, Q.; Ding, Y.; Yao, X., Characterizations of Hardy spaces associated to higher order elliptic operators, Journal of Functional Analysis, 263, 3, 604-674, (2012) · Zbl 1250.42078 · doi:10.1016/j.jfa.2012.05.001
[29] Stein, E. M., Harmonic Analysis, Real Variable Methods, Orthogonally, and Oscillatory Integrals, (1993), Princeton, NJ, USA: Princeton University Press, Princeton, NJ, USA
[30] Fefferman, C.; Stein, E., H_{p} spaces of several variables, Acta Mathematica, 129, 137-193, (1972) · Zbl 0257.46078
[31] Shui, P.-L.; Zhang, W.-C., Noise-robust edge detector combining isotropic and anisotropic Gaussian kernels, Pattern Recognition, 45, 2, 806-820, (2012) · Zbl 1225.68235 · doi:10.1016/j.patcog.2011.07.020
[32] Huixi, M., Commutators of generalized Hardy operators on homogeneous groups, Acta Mathematica Scientia. Series B, 30, 3, 897-906, (2010) · Zbl 1240.42057 · doi:10.1016/s0252-9602(10)60087-2
[33] Burkholder, R., The maximal Function characterization of the class \(\text{H}_{\text{p}}\), Transactions of the American Mathematical Society, 157, 137-153, (1971) · Zbl 0223.30048
[34] Tarel, J.-P.; Hautière, N.; Cord, A.; Gruyer, D.; Halmaoui, H., Improved visibility of road scene images under heterogeneous fog, Proceedings of the IEEE Intelligent Vehicles Symposium (IV ’10), IEEE · doi:10.1109/ivs.2010.5548128
[35] Wang, Y.-K.; Fan, C.-T., Single image defogging by multiscale depth fusion, IEEE Transactions on Image Processing, 23, 11, 4826-4837, (2014) · Zbl 1374.94403 · doi:10.1109/TIP.2014.2358076
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.