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http://dx.doi.org/10.5573/ieie.2017.54.1.088

Saliency Detection Using Entropy Weight and Weber's Law  

Lee, Ho Sang (Dept. Electronics Eng., Pusan National University)
Moon, Sang Whan (Dept. Electronics Eng., Pusan National University)
Eom, Il Kyu (Dept. Electronics Eng., Pusan National University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.54, no.1, 2017 , pp. 88-95 More about this Journal
Abstract
In this paper, we present a saliency detection method using entropy weight and Weber contrast in the wavelet transform domain. Our method is based on the commonly exploited conventional algorithms that are composed of the local bottom-up approach and global top-down approach. First, we perform the multi-level wavelet transform for the CIE Lab color images, and obtain global saliency by adding the local Weber contrasts to the corresponding low-frequency wavelet coefficients. Next, the local saliency is obtained by applying Gaussian filter that is weighted by entropy of wavelet high-frequency subband. The final saliency map is detected by non-lineally combining the local and global saliencies. To evaluate the proposed saliency detection method, we perform computer simulations for two image databases. Simulations results show the proposed method represents superior performance to the conventional algorithms.
Keywords
Saliency detection; wavelet transform; entropy weighted Gaussian kernel; Weber's contrast;
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