A novel image importance model for content-aware image resizing
Wonjun Kim, Changick Kim · 2011
This paper presents a novel method for adaptively resizing a given image to fit the dimensions of arbitrary displays. For the success of this content-aware image resizing, the image importance model needs to be carefully defined since it guides further resizing procedures. In our work, we focus on the excellence of the local dominance for measuring the image importance in a sense of human visual perception, which tends to strongly respond to the dominant structure in a local region. In contrast to most previous approaches not allowing for underlying image structure, the proposed model effectively represents the spatial contexts, which are indeed salient regions, even under severe distortion. The proposed method has been extensively tested and the results show that the proposed scheme is more effective for the image resizing when compared to various state-of-the-art methods.