Wavelet based seam carving for content-aware image resizing

In this paper, a novel content-aware image resizing method based on wavelet analysis is proposed. We estimate the local energy map of an image by weighing its multiscale subbands appropriately. Based on the energy map, the image is resized by repeatedly carving out or inserting in a connected path of pixels which is least significant in terms of the energy. Since wavelet analysis is similar to the way the human visual system operates, the obtained energy map reflects human perception with fidelity, and thus, the semantic information in the image can be preserved faithfully in the resizing process. The experimental results show that the proposed method produces higher subjective quality images than scaling and conventional content-aware image resizing techniques.