SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
High-quality video view interpolation using a layered representation
ACM SIGGRAPH 2004 Papers
2D/3D freeview video generation for 3DTV system
Image Communication
View generation with 3D warping using depth information for FTV
Image Communication
Depth-image-based rendering for 3DTV service over T-DMB
Image Communication
View synthesis prediction for multiview video coding
Image Communication
PCS'09 Proceedings of the 27th conference on Picture Coding Symposium
Free-viewpoint depth image based rendering
Journal of Visual Communication and Image Representation
FTV: Free-viewpoint Television
Image Communication
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Depth Image-Based Rendering With Advanced Texture Synthesis for 3-D Video
IEEE Transactions on Multimedia
Depth map misalignment correction and dilation for DIBR view synthesis
Image Communication
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Depth image based rendering is one of key techniques to realize view synthesis for three-dimensional television and free-viewpoint television, which provide high quality and immersive experiences to end viewers. However, artifacts of rendered images, including holes caused by occlusion/disclosure and boundary artifacts, may degrade the subjective and objective image quality. To handle these problems and improve the quality of rendered images, we present a novel view-spatial-temporal post-refinement method for view synthesis, in which new hole-filling and boundary artifact removal techniques are proposed. In addition, we propose an optimal reference frame selection algorithm for a better trade-off between the computational complexity and rendered image quality. Experimental results show that the proposed method can achieve a peak signal-to-noise ratio gain of 0.94dB on average for multiview video test sequences when compared with the benchmark view synthesis reference software. In addition, the subjective quality of the rendered image is also improved.