This Letter proposes a novel saliency detection method based on biological plausibility of a hypercomplex Fourier spectrum contrast algorithm. The proposed algorithm takes into consideration not only simulation of simple cortical cells in the receptive field of humans but also the texture-color feature global spectrum contrast of an image. First, we utilize log-Gabor filters to mimic simple cortical cells in the receptive field of humans. Two complex numbers of texture colors are acquired through feature maps in hue, saturation, and value color space by log-Gabor. Second, we build the hypercomplex number using these representations of feature maps. Finally, the salient object is detected by spectrum contrast in the hypercomplex Fourier domain. Experimental results show that the proposed algorithm outperforms the state-of-the-art methods.
© 2012 Optical Society of America
Original Manuscript: March 1, 2012
Revised Manuscript: July 11, 2012
Manuscript Accepted: July 12, 2012
Published: August 27, 2012
Vol. 7, Iss. 11 Virtual Journal for Biomedical Optics
Ce Li, Jianru Xue, Zhiqiang Tian, Lu Li, and Nanning Zheng, "Saliency detection based on biological plausibility of hypercomplex Fourier spectrum contrast," Opt. Lett. 37, 3609-3611 (2012)