Abstract
Pixel-based scale saliency (PSS) work bases on information estimation of data content and structure in multiscale analysis; its theoretical aspects as well as practical implementation are discussed by Kadir et al [11]. Scale Saliency framework [10] does not work only for pixels but other basis-projected descriptors as well. While wavelet atoms, localization in both time and frequency domain, are possible alternative descriptors, no theoretical analysis and practical solutions have been proposed yet. Our contribution is introducing a mathematical model of utilizing wavelet-based descriptors in a correspondent Wavelet-based Scale Saliency (WSS). It treats wavelet sub-band energy density of two popular discrete wavelet transform (DWT) and dual-tree complex wavelet transform (DTCWT) as basis descriptors instead of pixel-value descriptors for saliency map estimation. Then, ROC, AUC, and NSS quantitative analysis are comparing WSS against PSS as well as other state-of-the-art saliency methods ITT [9], SUN [18], SRS [8] on N. Bruce’s database [4] with human eye-tracking data as ground-truth. Furthermore, qualitative results, different saliency maps, are analyzed case by case for their pros and cons; especially their short-comings in specific situation or insensible results for human perception.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anh Cat, L.N., Qiu, G., Geoff, U., Li-minn, A., Kah Phooi, S.: Visual Information Based on Fast nonparametric multidimensional entropy estimation. International Conference on Acoustic, Speed and Signal Processing (1) (2012)
Baldi, P., Itti, L.: Of bits and wows: A Bayesian theory of surprise with applications to attention. Neural Networks: The Official Journal of the International Neural Network Society 23(5), 649–666 (2010)
Borji, A., Sihite, D.N., Itti, L.: Quantitative Analysis of Human-Model Agreement in Visual Saliency Modeling: A Comparative Study. IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society PP(99), 1–16 (2012)
Bruce, N.D.B., Tsotsos, J.K.: Saliency based on information maximization. In: Advances in Neural Information Processing Systems, vol. 18, p. 155 (2006)
Bruce, N.D.B., Tsotsos, J.K.: Saliency, attention, and visual search: An information theoretic approach. Journal of Vision 9, 1–24 (2009)
Chan, W.L., Choi, H., Baraniuk, R.G.: Coherent multiscale image processing using dual-tree quaternion wavelets. IEEE Transactions on Image Processing: A Publication of the IEEE Signal Processing Society 17(7), 1069–1082 (2008)
Gao, D., Mahadevan, V., Vasconcelos, N.: The discriminant center-surround hypothesis for bottom-up saliency. In: Advances in Neural Information Processing Systems, vol. 20, pp. 1–8 (2007)
Hou, X., Zhang, L.: Saliency detection: A spectral residual approach. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2007). No. 800, pp. 1–8. IEEE Computer Society, Citeseer (2007)
Itti, L., Koch, C., Niebur, E., et al.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998)
Kadir, T., Boukerroui, D., Brady, M.: An analysis of the scale saliency algorithm. OUEL No: 2264 3, 1–38 (2003)
Kadir, T., Brady, M.: Saliency, scale and image description. International Journal of Computer Vision 45(2), 83–105 (2001)
Qiu, G., Gu, X., Chen, Z., Chen, Q., Wang, C.: An information theoretic model of spatiotemporal visual saliency. To Appear, International Conference on Multimedia and Expo., pp. 1806–1809. Citeseer (2007)
Gilles, S.: Robust Description and Matching of Images. Ph.D. thesis, University of Oxford (1998)
Selesnick, I., Baraniuk, R., Kingsbury, N.: The dual-tree complex wavelet transform. IEEE Signal Processing Magazine 22(6), 123–151 (2005)
Starck, J., Murtagh, F.: Multiscale entropy filtering. Signal Processing 76 (1999)
Stowell, D., Plumbley, M.D.: Fast multidimensional entropy estimation by k-d partitioning. Signal Processing 16(6), 537–540 (2009)
Suau, P., Escolano, F.: A New Feasible Approach to Multi-dimensional Scale Saliency. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2009. LNCS, vol. 5807, pp. 77–88. Springer, Heidelberg (2009)
Zhang, L., Tong, M.H., Marks, T.K., Shan, H., Cottrell, G.W.: SUN: A Bayesian framework for saliency using natural statistics. Journal of Vision 8(7), 321–20 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Le Ngo, A.C., Ang, LM., Qiu, G., Seng, K.P. (2013). Information-Based Scale Saliency Methods with Wavelet Sub-band Energy Density Descriptors. In: Selamat, A., Nguyen, N.T., Haron, H. (eds) Intelligent Information and Database Systems. ACIIDS 2013. Lecture Notes in Computer Science(), vol 7803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36543-0_38
Download citation
DOI: https://doi.org/10.1007/978-3-642-36543-0_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36542-3
Online ISBN: 978-3-642-36543-0
eBook Packages: Computer ScienceComputer Science (R0)