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Proceedings Paper

An enhanced non local mean method for hole filling in the depth image-based rendering system
Author(s): Zihao Zhang D.D.S.; Yuanqing Wang Sr.; Lingli Zhan M.D.
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Paper Abstract

Depth image based rendering (DIBR) is the most widely used technology among synthesis algorithms. Hole filling is a challenge in producing desirable synthesized images. In this paper, we propose an enhanced non local mean based hole filling method. Color, gradient and depth information is combined to select the optimal candidate patches. The missing information from holes is then formed by aggregating multiple candidate patches. Furthermore, an efficient invalid pixel classification method based on their chararcteristics is proposed to divide invalid pixels into three types, and use different methods to fill them, and reduce the computational load of the hole filling unit. The results show that the proposed method has a better robustness and performance for hole filling in DIBR systems than other hole filling based on algorithms.

Paper Details

Date Published: 14 August 2019
PDF: 9 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 1117937 (14 August 2019); doi: 10.1117/12.2539754
Show Author Affiliations
Zihao Zhang D.D.S., Nanjing Univ. (China)
Yuanqing Wang Sr., Nanjing Univ. (China)
Lingli Zhan M.D., Nanjing Univ. (China)

Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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