TY - GEN
T1 - Efficient hole filling and depth enhancement based on texture image and depth map consistency
AU - Chang, Ting An
AU - Kuo, Jung Ping
AU - Yang, Jar Ferr
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/3
Y1 - 2017/1/3
N2 - Structured-light RGB-D cameras are commonly used to capture depth images, which convey the per-pixel depth information in a scene. However, these cameras often produce regions with missing pixels. The missing pixel regions, which refer to holes, will not contain any depth information for the depth image. This reason would lead the performance to degrade seriously in modern-day three-dimensional (3D) video applications. Therefore, how to effectively utilize image information and depth maps become more and more important. In this paper, we propose adaptive texture-similarity-based hole filling (ATSHF) and adaptive texture-similarity-based depth enhancement (ATSDE). The proposed system, which is used for the enhancement of depth maps, is achieved by suppressing the noise, filling holes and sharpening object edges simultaneously. Experimental results demonstrate that the proposed method provides a superior performance, especially around the object boundary. Beside, we compare with the other state-of-the-art methods about the image and the depth map enhancement.
AB - Structured-light RGB-D cameras are commonly used to capture depth images, which convey the per-pixel depth information in a scene. However, these cameras often produce regions with missing pixels. The missing pixel regions, which refer to holes, will not contain any depth information for the depth image. This reason would lead the performance to degrade seriously in modern-day three-dimensional (3D) video applications. Therefore, how to effectively utilize image information and depth maps become more and more important. In this paper, we propose adaptive texture-similarity-based hole filling (ATSHF) and adaptive texture-similarity-based depth enhancement (ATSDE). The proposed system, which is used for the enhancement of depth maps, is achieved by suppressing the noise, filling holes and sharpening object edges simultaneously. Experimental results demonstrate that the proposed method provides a superior performance, especially around the object boundary. Beside, we compare with the other state-of-the-art methods about the image and the depth map enhancement.
UR - http://www.scopus.com/inward/record.url?scp=85011103498&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85011103498&partnerID=8YFLogxK
U2 - 10.1109/APCCAS.2016.7803930
DO - 10.1109/APCCAS.2016.7803930
M3 - Conference contribution
AN - SCOPUS:85011103498
T3 - 2016 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2016
SP - 192
EP - 195
BT - 2016 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2016
Y2 - 25 October 2016 through 28 October 2016
ER -