中文摘要：

Visual saliency is an important cue in human visual system to identify salient region in the image;it can be useful in many applications including image retrieval,object recognition,image segmentation,etc.Image contrast has been used as an effective feature to detect visual salient region.However,the conventional contrast measures either in spectral domain or in spatial domain fail to give sufficient consideration towards the local and global characteristics of the image.This paper presents a visual saliency detection algorithm based on a novel contrast measurement.This measurement extracts the spectral information of image block using the 2D discrete Fourier transform(DFT),and combines with the total variation(TV)of image block in spatial domain.The proposed algorithm is used to perform salient region detection in the image,and compared with state-of-the-art algorithms.The experimental results from the MSRA dataset validate the effectiveness of the proposed algorithm.更多还原

英文摘要：

Visual saliency is an important cue in human visual system to identify salient region in the image; it can be useful in many applications including inmge retrieval, object recognition, image segmentation, etc. Image contrast has been used as an effective feature to detect visual salient region. However, the conventional contrast measures either in spectral domain or in spatial domain fail to give sufficient consideration towards the local and global characteristics of the image. This paper presents a visual saliency detection algorithm based on a novel contrast measurement. This measurement extracts the spectral information of image block using the 2D discrete Fourier transform （DFT）, and combines with the total variation （TV） of image block in spatial domain. The proposed algorithm is used to perform salient region detection in the image, and compared with state-of-the-art algorithms. The experimental results from the MSRA dataset validate the effectiveness of the proposed algorithm. Key words： visual saliencv, contrast measure, multi-,~e~lo, lne~l c（mtrn~t ~lahnl cnntr~t-