@techreport{oai:ipsj.ixsq.nii.ac.jp:00090898,
 author = {Ahmed, Boudissa and JooKooiTan and Hyoungseop, Kim and Seiji, Ishikawa and Takshi, Shinomiya and Ahmed, Boudissa and Joo, KooiTan and Hyoungseop, Kim and Seiji, Ishikawa and Takshi, Shinomiya},
 issue = {18},
 month = {Mar},
 note = {In this paper, we present a novel approach to saliency detection. The method we propose here aims at synthesizing common knowledge of saliency in an image. We define a visually salient region with following two parameters; the spatial redundancy and its local appearance. The former is its probability of occurrence within the image, which is a quantification of the “rarity” of the concerned region, whereas the latter defines how much information is contained within the region, and it can be quantified using the entropy. By combining the global spatial redundancy measure and local entropy, we can achieve a simple, yet robust measure. We evaluated and compared it to Itti's and the spectral residual methods, and it has shown a significant improvement of performance., In this paper, we present a novel approach to saliency detection. The method we propose here aims at synthesizing common knowledge of saliency in an image. We define a visually salient region with following two parameters; the spatial redundancy and its local appearance. The former is its probability of occurrence within the image, which is a quantification of the “rarity” of the concerned region, whereas the latter defines how much information is contained within the region, and it can be quantified using the entropy. By combining the global spatial redundancy measure and local entropy, we can achieve a simple, yet robust measure. We evaluated and compared it to Itti's and the spectral residual methods, and it has shown a significant improvement of performance.},
 title = {A novel saliency measure using combined spatial redundancy and local appearance},
 year = {2013}
}