@article{SisLab3454,
           title = {A Novel Fusion Method for 3D-TV View Synthesis Using Temporal and Disparity Correlations},
          author = {Trieu Duong Dinh and Minh Le Dinh and Jeon Byeungwoo and Van Xiem Hoang},
       publisher = {The Institute of Electronics and Information Engineers (IEIE)},
            year = {2019},
         journal = {IEIE Trans. on Smart Processing and Computing},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3454/},
        abstract = {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.}
}