Content-aware image resizing is a kind of new and effective approach for image resizing, which preserves image content well and does not cause obvious distortion when changing the aspect ratio of images. Recently, a seam based approach for content-aware image resizing was proposed by Avidan and Shamir. Their results are impressive, but because the method uses dynamic programming many times, it is slow. In this paper, we present a more efficient algorithm for seam based content-aware image resizing, which searches seams through establishing the matching relation between adjacent rows or columns. We give a linear algorithm to find the optimal matches within a weighted bipartite graph composed of the pixels in adjacent rows or columns. Therefore, our method is fast (e.g. our method needs only about 100 ms to reduce a 768 × 1024 image’s width to 1/3 while Avidan and Shamir’s method needs 12 s). This supports immediate image resizing whereas Avidan and Shamir’s method requires a more costly pre-processing step to enable subsequent real-time processing. A fast method such as the one proposed will be also needed for future real-time video resizing applications.
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Supported by National Natural Science Foundation of China (Grant Nos. 60575002 and 60641002)
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Huang, H., Fu, T., Rosin, P.L. et al. Real-time content-aware image resizing. Sci. China Ser. F-Inf. Sci. 52, 172 (2009). https://doi.org/10.1007/s11432-009-0041-9
- content aware
- image resizing
- video resizing
- real time