A method for filtering smoke in images
Resumo
The treatment of images captured in situations where there the we have bad visibility like smoke or foggy weather conditions is a great challenge. In this sense, we have developed a technique of filtering smoke and foggy in images that have the potential to benefit many applications of understanding and computational vision. Our algorithm is based on a series of mathematical methods to capture the noise by means of its density, in the end our results demonstrate that the method is quite effective to solve the problem of the test images.
Referências
Ancuti, C. O. and Ancuti, C. (2013). Single image dehazing by multi-scale fusion. IEEE Transactions on Image Processing, 22(8):3271–3282.
Berman, D., Avidan, S., et al. (2016). Non-local image dehazing. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1674–1682.
Cai, B., Xu, X., Jia, K., Qing, C., and Tao, D. (2016). Dehazenet: An end-to-end system for single image haze removal. IEEE Transactions on Image Processing, 25(11):5187– 5198.
Fattal, R. (2008). Single image dehazing. ACM transactions on graphics (TOG), 27(3):72.
Han, J., Ji, X., Hu, X., Zhu, D., Li, K., Jiang, X., Cui, G., Guo, L., and Liu, T. (2013).
Representing and retrieving video shots in human-centric brain imaging space. IEEE Transactions on Image Processing, 22(7):2723–2736.
He, K., Sun, J., and Tang, X. (2011). Single image haze removal using dark channel prior. IEEE transactions on pattern analysis and machine intelligence, 33(12):2341–2353.
Jiang, J., Hou, T., and Qi, M. (2011). Improved algorithm on image haze removal using dark channel prior. Journal of circuits and systems, 16(2):7–12.
Kratz, L. and Nishino, K. (2009). Factorizing scene albedo and depth from a single foggy image. In Computer Vision, 2009 IEEE 12th International Conference on, pages 1701– 1708. IEEE.
Liu, L. and Shao, L. (2013). Learning discriminative representations from rgb-d video data. In IJCAI, volume 1, page 3.
Meng, G., Wang, Y., Duan, J., Xiang, S., and Pan, C. (2013). Efficient image dehazing
with boundary constraint and contextual regularization. In Computer Vision (ICCV), 2013 IEEE International Conference on, pages 617–624. IEEE.
Narasimhan, S. (2004). Models and Algorithms for Vision Through the Atmospere. Columbia University.
Narasimhan, S. G. and Nayar, S. K. (2003). Contrast restoration of weather degraded images. IEEE transactions on pattern analysis and machine intelligence, 25(6):713– 724.
Shao, L., Liu, L., and Li, X. (2014). Feature learning for image classification via multiobjective genetic programming. IEEE Transactions on Neural Networks and Learning Systems, 25(7):1359–1371.
Stark, J. A. (2000). Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Transactions on image processing, 9(5):889–896.
Wang, W., Yuan, X., Wu, X., Liu, Y., and Ghanbarzadeh, S. (2016). An efficient method for image dehazing. In Image Processing (ICIP), 2016 IEEE International Conference on, pages 2241–2245. IEEE.
Woodell, G., Jobson, D. J., Rahman, Z.-u., and Hines, G. (2006). Advanced image processing of aerial imagery. In Visual Information Processing XV, volume 6246, page 62460E. International Society for Optics and Photonics.
Xie, B., Guo, F., and Cai, Z. (2010). Improved single image dehazing using dark channel prior and multi-scale retinex. In Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on, volume 1, pages 848–851. IEEE.
Zhu, Q., Mai, J., and Shao, L. (2015). A fast single image haze removal algorithm using color attenuation prior. IEEE Transactions on Image Processing, 24(11):3522–3533.
Berman, D., Avidan, S., et al. (2016). Non-local image dehazing. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1674–1682.
Cai, B., Xu, X., Jia, K., Qing, C., and Tao, D. (2016). Dehazenet: An end-to-end system for single image haze removal. IEEE Transactions on Image Processing, 25(11):5187– 5198.
Fattal, R. (2008). Single image dehazing. ACM transactions on graphics (TOG), 27(3):72.
Han, J., Ji, X., Hu, X., Zhu, D., Li, K., Jiang, X., Cui, G., Guo, L., and Liu, T. (2013).
Representing and retrieving video shots in human-centric brain imaging space. IEEE Transactions on Image Processing, 22(7):2723–2736.
He, K., Sun, J., and Tang, X. (2011). Single image haze removal using dark channel prior. IEEE transactions on pattern analysis and machine intelligence, 33(12):2341–2353.
Jiang, J., Hou, T., and Qi, M. (2011). Improved algorithm on image haze removal using dark channel prior. Journal of circuits and systems, 16(2):7–12.
Kratz, L. and Nishino, K. (2009). Factorizing scene albedo and depth from a single foggy image. In Computer Vision, 2009 IEEE 12th International Conference on, pages 1701– 1708. IEEE.
Liu, L. and Shao, L. (2013). Learning discriminative representations from rgb-d video data. In IJCAI, volume 1, page 3.
Meng, G., Wang, Y., Duan, J., Xiang, S., and Pan, C. (2013). Efficient image dehazing
with boundary constraint and contextual regularization. In Computer Vision (ICCV), 2013 IEEE International Conference on, pages 617–624. IEEE.
Narasimhan, S. (2004). Models and Algorithms for Vision Through the Atmospere. Columbia University.
Narasimhan, S. G. and Nayar, S. K. (2003). Contrast restoration of weather degraded images. IEEE transactions on pattern analysis and machine intelligence, 25(6):713– 724.
Shao, L., Liu, L., and Li, X. (2014). Feature learning for image classification via multiobjective genetic programming. IEEE Transactions on Neural Networks and Learning Systems, 25(7):1359–1371.
Stark, J. A. (2000). Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Transactions on image processing, 9(5):889–896.
Wang, W., Yuan, X., Wu, X., Liu, Y., and Ghanbarzadeh, S. (2016). An efficient method for image dehazing. In Image Processing (ICIP), 2016 IEEE International Conference on, pages 2241–2245. IEEE.
Woodell, G., Jobson, D. J., Rahman, Z.-u., and Hines, G. (2006). Advanced image processing of aerial imagery. In Visual Information Processing XV, volume 6246, page 62460E. International Society for Optics and Photonics.
Xie, B., Guo, F., and Cai, Z. (2010). Improved single image dehazing using dark channel prior and multi-scale retinex. In Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on, volume 1, pages 848–851. IEEE.
Zhu, Q., Mai, J., and Shao, L. (2015). A fast single image haze removal algorithm using color attenuation prior. IEEE Transactions on Image Processing, 24(11):3522–3533.
Publicado
16/10/2018
Como Citar
OLIVEIRA, Marcos ; SILVA, Francisco; SARAIVA, Arata ; FERREIRA, Nuno; SOUSA, José.
A method for filtering smoke in images. In: ESCOLA REGIONAL DE INFORMÁTICA DO PIAUÍ (ERI-PI), 4. , 2018, Teresina.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 7 - 12.
