Paper:
Representing Visual Complexity of Images Using a 3D Feature Space Based on Structure, Noise, and Diversity
Phuc Q. Le, Abdullah M. Iliyasu, Jesus A. Garcia Sanchez,
Fangyan Dong, and Kaoru Hirota
Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
- [1] M. Cardici, V. D. Gesu, M. Petrou, and M. E. Tabacchi, “A Fuzzy Approach to the Evaluation of Image Complexity,” Fuzzy Sets and Systems, pp. 1474-1484, Vol.160, 2009.
- [2] F. Yaghmaee and M. Jamzad, “Computing Watermark Capacity in Images according to their Quad Tree,” Int. Symposium on Signal Processing and Information Technology, 2005.
- [3] M. Jamzad and F. Yaghmaee, “Using Image Complexity according to Achieving Higher Stability in Digital Watermarking,” Int. Conf. ICIRA, 2004.
- [4] Q. Liu, A. H. Sung, B. Ribeiro, M.Wei, Z. Chen, and J. Xu, “Image Complexity and Feature Mining for Steganalysis of Least Significant Bit Matching Steganography,” Int. J. of Information Sciences, Vol.178, pp. 21-36, 2008.
- [5] I. Mario, M. Chacon, D. Alma, and S. Corral, “Image Complexity Measure: a Human Criterion Free Approach,” Proc. NAFIPS2005, pp. 241-246, 2005.
- [6] J. Rigau, M. Feixas, and M. Sbert, “An Information-Theoretic Framework for Image Complexity, Computational Aesthetics in Graphics, Visualization and Images,” pp. 177-184, 2005.
- [7] S. Tai and S. Yang, “A Fast Method for Image Noise Estimation using Laplacian Operator and Adaptive Edge Detection,” ISCCSP, 2008.
- [8] E. Rosten, R. Porter, and T. Drummond, “Fast and Better: a Machine Learning Approach to Corner Detection,” ISCCSP, 2008.
- [9] P. Q. Le, A. M. Iliyasu, A. S. Garcia, F. Dong, and K Hirota, “A Three Dimensional Feature Space for Representing Visual Complexity of Images using their Structure, Noise, and Diversity,” Proc. ISIS 2011, pp. 417-420, 2011.
- [10] http://www-db.stanford.edu/w˜angz/image.vary.tar, Accessed, 2011.
- [11] G. Griffin, A. D. Holub, and P. Perona, “The Caltech-256,” Caltech Technical Report.
http://www.vision.caltech.edu/Image_Datasets/Caltech256,
Accessed, 2011.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.