Reflection Removal

  • Reflection removal for 2D images

The images taken through glass often capture a target transmitted scene as well as undesired reflected scenes. In this paper, we propose an optimization problem to remove reflection automatically from multiple glass images taken at slightly different camera locations. We first warp the multiple glass images to a reference image, where the gradients are consistent in the transmission images while the gradients are varying across the reflection images. Based on this observation, we compute a gradient reliability such that the pixels belonging to the salient edges of the transmission image are assigned high reliability, but that of the reflection images are assigned low values. Then we suppress the gradients of the reflection images and recover the gradients of the transmission images only, by solving the proposed optimization problem in gradient domain. We reconstruct an original transmission image using the resulting optimal gradient map. Experimental results show that the proposed algorithm removes the reflection artifacts from glass images faithfully and outperforms the existing algorithms.

  • Reflection removal for 3D point clouds

Large-scale 3D point clouds (LS3DPCs) captured by terrestrial LiDAR scanners often exhibit reflection artifacts by glasses, which degrade the performance of related computer vision techniques. In this paper, we propose an efficient reflection removal algorithm for LS3DPCs. We first partition the unit sphere into local surface patches which are then classified into the ordinary patches and the glass patches according to the number of echo pulses from emitted laser pulses. Then we estimate the glass region of dominant reflection artifacts by measuring the reliability. We also detect and remove the virtual points using the conditions of the reflection symmetry and the geometric similarity. We test the performance of the proposed algorithm on LS3DPCs capturing real-world outdoor scenes, and show that the proposed algorithm estimates valid glass regions faithfully and removes the virtual points caused by reflection artifacts successfully.

  • Publications
[1] Byeong-Ju Han and Jae-Young Sim, “Reflection removal using low-rank matrix completion,” in Proc. IEEE CVPR, Honolulu, USA, July 2017. [more]
[2] Jae-Seong Yun and Jae-Young Sim, “Reflection removal for large-scale 3D point clouds,” in Proc. IEEE CVPR, Salt Lake City, USA, June 2018. [more]