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On measuring low-level saliency in photographic images

Measuring perceptual saliency of regions in a scene is important for determining regions of interest. Color, texture and shape cues are good low-level features for detecting saliency. While self saliency refers to intrinsic attributes of a region, relative saliency as used to measure how salient a region is relative to its surrounding and, thus, needs to be defined within a spatial context. A few spatial context models are investigated in this study. In particular, we propose an auto-scaled, amorphous neighborhood as the context model to obtain reliable measurements of relative saliency features. Comparison of three context models has shown that the proposed model is capable of generating predicates more consistent with perceived saliency.