@article{2eb3898c737449c2b15f752299d1500b,
title = "Depth map enhancement using adaptive moving least squares method with a total variation minimization",
abstract = "Accurate and fast depth map acquisition and enhancement is an important issue in the area of computer vision and image processing. In this study, we present a novel method for enhancing noisy depth maps using adaptive total variation minimization, which facilitates noise smoothing and boundary sharpening for a given depth map image but without previous information. We filter the noise in the depth map with a refined total variation minimization technique. Our experimental results demonstrate that the proposed method outperforms other competitive methods in both objective and subjective comparisons of depth map enhancement and denoising.",
keywords = "Image denoising, Total variation minimization",
author = "Yoon, {Sang Min} and Jungho Yoon",
note = "Funding Information: S.M. Yoon was supported by the ICT R&D program of MSIP/IITP, Korea (B0101-15-1347), A Study on the Key Technology of Optical Modulation and Signal Processing for Implementation of 400 Gb/s Optical Transmission. S.M. Yoon was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF--2014R1A1A1002890). Jungho Yoon was supported by NRF20151009350 (Science Research Center Program) and 2009–0093827 (Priority Research Centers Program) through the National Research Foundation of Korea. Publisher Copyright: {\textcopyright} 2015, Springer Science+Business Media New York.",
year = "2016",
month = dec,
day = "1",
doi = "10.1007/s11042-015-2905-x",
language = "English",
volume = "75",
pages = "15929--15938",
journal = "Multimedia Tools and Applications",
issn = "1380-7501",
publisher = "Springer Netherlands",
number = "23",
}