An Improved Saliency Detection for Different Light Conditions

• Yongfeng Ren,
• Jingbo Zhou,
• Zhijian Wang,
• Yunyang Yan,

Vol. 9, No. 3, March 30, 2015
10.3837/tiis.2015.03.018, Download Paper (Free):

• Saliency detection
• Local sensitive histograms
• Illumination invariant features
• Different light conditions

Abstract

In this paper, we propose a novel saliency detection framework based on illumination invariant features to improve the accuracy of the saliency detection under the different light conditions. The proposed algorithm is divided into three steps. First, we extract the illuminant invariant features to reduce the effect of the illumination based on the local sensitive histograms. Second, a preliminary saliency map is obtained in the CIE Lab color space. Last, we use the region growing method to fuse the illuminant invariant features and the preliminary saliency map into a new framework. In addition, we integrate the information of spatial distinctness since the saliency objects are usually compact. The experiments on the benchmark dataset show that the proposed saliency detection framework outperforms the state-of-the-art algorithms in terms of different illuminants in the images.

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