Parallel Accelerated Matting Method Based on Local Learning

Xiaoqiang Li, Qing Cui

Abstract: To pursue effective and fast matting method is of great importance in digital image editing. This paper proposes a scheme to accelerate learning based digital matting and implement it on modern GPU in parallel, which involves learning stage and solving stage. Firstly, we present GPU-based method to accelerate the pixel-wise learning stage. Then, trimap skeleton based algorithm is proposed to divide the image into blocks and process blocks in parallel to speed up the solving stage. Experimental results demonstrated that the proposed scheme achieves a maximal 12+ speedup over previous serial methods without degrading segmentation precision.