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14 August 2019 An enhanced non local mean method for hole filling in the depth image-based rendering system
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Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 1117937 (2019) https://doi.org/10.1117/12.2539754
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zihao Zhang D.D.S., Yuanqing Wang Sr., and Lingli Zhan M.D. "An enhanced non local mean method for hole filling in the depth image-based rendering system", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 1117937 (14 August 2019); https://doi.org/10.1117/12.2539754
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