TY  - JOUR
ID  - SisLab3454
UR  - http://www.ieiespc.org/
A1  - Dinh, Trieu Duong
A1  - Le Dinh, Minh
A1  - Byeungwoo, Jeon
A1  - Hoang, Van Xiem
Y1  - 2019///
N2  - View synthesis like Depth-image-based-rendering (DIBR) plays a significant role in 3D content creation for 3D-TV. However, perceptual errors introduced by current view synthesis often result in severe distortions in synthesized images. In this paper, we propose a novel view synthesis fusion (VSF) method which adaptively exploits temporal and disparity correlations to improve the quality of the synthesized picture. The proposed VSF method defines a robust correlation assessment metric for fusing several pre-created virtual view candidates. Unlike conventional methods, the proposed fusion algorithm is applied for both hole and non-hole areas. Experimental results show significantly outperforming peak signal-to noise ratio (PSNR) and subjective visual quality by the proposed method compared to other conventional methods.
PB  - The Institute of Electronics and Information Engineers (IEIE)
JF  - IEIE Trans. on Smart Processing and Computing
SN  - 2287-5255
TI  - A Novel Fusion Method for 3D-TV View Synthesis Using Temporal and Disparity Correlations
AV  - public
ER  -