Multi-Resolution Salient Region Detection in Frequency Domain

Yingchun Guo, Yanhong Feng, Gang Yan and Shuo Shi
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Yingchun Guo: School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China
Yanhong Feng: School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China
Gang Yan: School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China
Shuo Shi: School of Computer Science and Engineering, Hebei University of Technology, Tianjin, China

International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), 2014, vol. 6, issue 1, 60-70

Abstract: Salient region detection is a challenge problem in computer vision, which is useful in image segmentation, region-based image retrieval, and so on. In this paper we present a multi-resolution salient region detection method in frequency domain which can highlight salient regions with well-defined boundaries of object. The original image is sub-sampled into three multi-resolution layers, and for each layer the luminance and color salient features are extracted in frequency domain. Then, the significant values are calculated by using invariant laws of Euclidean distance in Lab space and the normal distribution function is used to specify the salient map in each layer in order to remove noise and enhance the correlation among the vicinity pixels. The final saliency map is obtained by normalizing and merging the multi-resolution salient maps. Experimental evaluation depicts the promising results from the proposed model by outperforming the state-of-art frequency-tuned model.

Date: 2014
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