Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Accurate and high-quality depth maps are required in lots of 3D applications, such as multi-view rendering, 3D reconstruction and 3DTV. Hover, the resolution of captured depth image is much lor than that of its corresponding color image, which affects its application performance. ,  propose a novel depth map super-resolution (SR) method by taking view synthesis quality into account. The proposed approach mainly includes two technical contributions. First, since the captured low-resolution (LR) depth map may be corrupted by noise and occlusion,  propose a credibility based multi-view depth maps fusion strategy, which considers the view synthesis quality and interview correlation, to refine the LR depth map. Second,  propose a view synthesis quality based trilateral depth-map up-sampling method, which considers depth smoothness, texture similarity and view synthesis quality in the up-sampling filter. Experimental results demonstrate that the proposed method outperforms state-of-the-art depth SR methods for both super-resolved depth maps and synthesized views. Furthermore, the proposed method is robust to noise and achieves promising results under noise-corruption conditions.
['Jianjun Lei', 'Lele Li', 'Huanjing Yue', 'Feng Wu', 'Nam Ling', 'Chunping Hou']
I am writing a research paper on a idea Depth Map Super-Resolution Considering View Synthesis Quality
[{"from": "human", "value": "I am writing a research paper on a idea Depth Map Super-Resolution Considering View Synthesis Quality"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Accurate and high-quality depth maps are required in lots of 3D applications, such as multi-view rendering, 3D reconstruction and 3DTV. Hover, the resolution of captured depth image is much lor than that of its corresponding color image, which affects its application performance. ,  propose a novel depth map super-resolution (SR) method by taking view synthesis quality into account. The proposed approach mainly includes two technical contributions. First, since the captured low-resolution (LR) depth map may be corrupted by noise and occlusion,  propose a credibility based multi-view depth maps fusion strategy, which considers the view synthesis quality and interview correlation, to refine the LR depth map. Second,  propose a view synthesis quality based trilateral depth-map up-sampling method, which considers depth smoothness, texture similarity and view synthesis quality in the up-sampling filter. Experimental results demonstrate that the proposed method outperforms state-of-the-art depth SR methods for both super-resolved depth maps and synthesized views. Furthermore, the proposed method is robust to noise and achieves promising results under noise-corruption conditions."}]