Optimizing Seam Carving on multi-GPU systems for real-time image resizing

Abstract

Image resizing is increasingly important for picture sharing and exchanging between various personal electronic equipments. Seam Carving is a state-of-the-art approach for effective image resizing because of its content-aware characteristic. However, complex computation and memory access patterns make it time-consuming and prevent its wide usage in real-time image processing. To address these problems, we propose a novel algorithm, called Non-Cumulative Seam Carving (NCSC), which removes main computation bottleneck. Furthermore, we also propose an adaptive multi-seam algorithm for better parallelism on GPU platforms. Finally, we implement our algorithm on a multi-GPU platform. Results show that our approach achieves a maximum 140× speedup on a two-GPU system over the sequential version. It only takes 0.11 second to resize a 1024×640 image by half in width compared to 15.5 seconds with the traditional seam carving.

Publication
2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)
Jidong Zhai
Jidong Zhai
Associate Professor
(特别研究员、博士生导师)
Wenguang Chen
Wenguang Chen
Professor
(教授)