Li, Y., Li, Z., Zheng, C., & Wu, S. (2022). Adaptive weighted guided image filtering for depth enhancement in shape-from-focus. Pattern Recognition, 131, 108900. https://doi.org/10.1016/j.patcog.2022.108900
Existing shape from focus (SFF) techniques cannot preserve depth edges and fine structural details from a sequence of multi-focus images. Moreover, noise in the sequence affects the accuracy of the depth map. In this paper, a novel depth enhancement algorithm for the SFF based on an adaptive weighted guided image filtering (AWGIF) is proposed to address the above issues. The AWGIF is applied to decompose an initial depth map estimated by the traditional SFF into base and detail layers. In order to preserve the edges accurately in the refined depth map, the guidance image is constructed from the sequence, and the coefficient of the AWGIF is utilized to suppress the noise while enhancing the fine depth details. Experiments on real and synthetic objects demonstrate the superiority of our algorithm in terms of anti- noise, and the ability to preserve depth edges and fine structural details w.r.t. existing methods.
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
This work was supported by the National Natural Science Foundation of China (Grant NO. 61775172) and the Science Foundation of Education Department of Jiangxi Province (Grant No. GJJ201927)