Abstract
It brings great difficulty for salient object detection on the road under foggy weather, owing to the low contrast and the low resolution of fog-degraded image. The traditional methods of saliency detection such as spectral residual approach and phase spectrum approach are out of work. According to this problem, a new hierarchical saliency detection approach based on transmission information of foggy images is proposed, which fuses the spectral residual and phase spectrum under transmission information with a new weighted fusing approach. The experiments show that the proposed method can detect salient object such as pedestrians and vehicles on the road more effectively than independent spectral residual and phase spectrum approach, even under heavy fog condition.
This work is supported by National Natural Science Foundation (NNSF) of China under Grant 61403119 and Natural Science Foundation of Hebei Province under Grant F201402166 and F2015202231.
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References
Cheng, M., Zhang, G., Mitra, N., Huang, X., Hu, S.: Global contrast based salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 409–416 (2011)
Borji, A., Sihite, D.N., Itti, L.: Salient object detection: a benchmark. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7573, pp. 414–429. Springer, Heidelberg (2012)
Gao, D., Vasconcelos, N.: Discriminant saliency for visual recognition from cluttered scenes. In: Advances in neural information processing systems, pp. 481–488 (2004)
Schwartz, S., Wong, A.: Saliency-guided compressive sensing approach to efficient laser range measurement. J. Vis. Commun. Image Represent. 24(2), 160–170 (2012)
Itti, L., Koch, C.: Computational modelling of visual attention. Nat. Rev. Neurosci. 2(3), 194–203 (2001)
Hou, X., Zhang, L.: Saliency detection: a spectral residual approach. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)
Guo, C., Ma, Q., Zhang, L.: Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Narsimhan, G., Nayar, S.K.: Vision and the atmosphere. Int. J. Comput. Vis. 48(3), 233–254 (2002)
He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341–2353 (2011)
He, K., Sun, J., Tang, X.: Guided image filtering. IEEE Trans. Pattern Anal. Mach. Intell. 35(6), 1397–1409 (2013)
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Liu, K., Tian, J., Su, Xp., Zhou, Yq., Wang, J. (2016). Hierarchical Saliency Detection Under Foggy Weather Fusing Spectral Residual and Phase Spectrum. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 663. Springer, Singapore. https://doi.org/10.1007/978-981-10-3005-5_17
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DOI: https://doi.org/10.1007/978-981-10-3005-5_17
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