TY - JOUR
T1 - Robust depth enhancement based on texture and depth consistency
AU - Chang, Ting An
AU - Liao, Wei Chen
AU - Yang, Jar Ferr
N1 - Funding Information:
This work was supported in part by the National Science Council of Taiwan, under grant no. NSC 105-2221-E-006-065-MY3
Publisher Copyright:
© The Institution of Engineering and Technology.
PY - 2018/2/1
Y1 - 2018/2/1
N2 - With advances in three-dimension television (3DTV) technology, accurate depth information for 3DTV broadcasting has gained much attention recently. The depth map, either retrieved by stereo matching or captured by the RGB-D camera, is mostly with lower resolution and often with noisy or missing values than the texture frame. How to effectively utilise high-resolution texture image to enhance the corresponding depth map becomes an important and inevitable approach. In this study, the authors propose texture similarity-based hole filling, texture similarity-based depth enhancement and rotating counsel depth refinement to enhance the depth map. Thus, the proposed depth enhancement system could suppress the noise, fill the holes and sharpen the object edges simultaneously. Experimental results demonstrate that the proposed system provides a superior performance, especially around the object boundary comparing to the state-of-the-art depth enhancement methods.
AB - With advances in three-dimension television (3DTV) technology, accurate depth information for 3DTV broadcasting has gained much attention recently. The depth map, either retrieved by stereo matching or captured by the RGB-D camera, is mostly with lower resolution and often with noisy or missing values than the texture frame. How to effectively utilise high-resolution texture image to enhance the corresponding depth map becomes an important and inevitable approach. In this study, the authors propose texture similarity-based hole filling, texture similarity-based depth enhancement and rotating counsel depth refinement to enhance the depth map. Thus, the proposed depth enhancement system could suppress the noise, fill the holes and sharpen the object edges simultaneously. Experimental results demonstrate that the proposed system provides a superior performance, especially around the object boundary comparing to the state-of-the-art depth enhancement methods.
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U2 - 10.1049/iet-spr.2016.0550
DO - 10.1049/iet-spr.2016.0550
M3 - Article
AN - SCOPUS:85041658990
SN - 1751-9675
VL - 12
SP - 119
EP - 128
JO - IET Signal Processing
JF - IET Signal Processing
IS - 1
ER -