Abstract: Traditional global optimization based stereo matching methods generally have difficulties in processing high-resolution images,due to their high computational complexity and large memory space requirement.This paper proposes a novel detail-preserving hierarchical multi-view stereo matching method.In the proposed method,for each segmented image,we first evaluate the degree of fine structures and assign each segment with an appropriate resolution level for matching.Then,we perform a coarse-to-fine disparity estimation on the pyramid structure of the image.For each resolution level,we estimate the disparity with global optimization for the regions with corresponding level label,so that fine structures can be processed with appropriate resolutions.For regions processed in previous resolution levels,we just conduct a further disparity refinement.In addition,a block-based solving strategy is proposed,which divides the high-resolution image into multiple blocks,so that the global optimization algorithm can be performed with small memory space.The experimental results demonstrate that the proposed method is very efficient while preserving fine structures.