Divide-and-conquer Method with Refined Trimap for High-resolution Image Matting

Abstract

High-resolution image matting requires a substantial memory capacity. Therefore, it is very difficult to perform a high-resolution image matting, e.g. KNN image matting, in a common computing environment. This dissertation presents a simple yet novel methodology to solve a memory shortage issue involved in a high-resolution image matting with application of the divide-and-conquer method and a refined trimap. We use a refined trimap to minimize the potential quality degradation in the implementation of the divide-and-conquer method. A confidence map is computed by comparing the original input image and down-sampled image with lower resolution, and the confidence map is used to judge the reliability of the multigrid method in refining the trimap. The original input image is divided into fragments and individual alpha matte is computed with the refined trimap (fragment-level matting)

each fragment includes a margin overlapping with nearby fragment(s). Then, we merge the fragments in consideration of the overlapping margin to make sure the merged image does not suffer from discontinuity among fragments. This is the refined D-C method dealing with high-resolution image matting regardless of matting method. We propose this fast and versatile method for high-resolution image matting. This method protects users from potential memory shortage while obtaining a reasonable-quality alpha matte from a high-resolution image.