Depth image based rendering （DIBR） is an effective approach for virtual view synthesis in free viewpoint television and 3D video.One of the important steps in DIBR is filling the holes caused by disoeclusion regions...Depth image based rendering （DIBR） is an effective approach for virtual view synthesis in free viewpoint television and 3D video.One of the important steps in DIBR is filling the holes caused by disoeclusion regions and wrong depth values.Most of the existing hole-filling methods work well in areas of low spatial activity but fail to obtain satisfactory results in high spatial activity regions.In this paper,we combine the depth based hole-filling and the adaptive recursive interpolation algorithm which is capable of handling edges passing through the missing areas.Accoring to the experimental results,we confirm that the depth based adaptive recursive interpolation algorithm can provide better rendering quality objectively and subjectively.展开更多
In order to solve the hole-filling mismatch problem in virtual view synthesis, a three-step repairing(TSR) algorithm was proposed. Firstly, the image with marked holes is decomposed by the non-subsampled shear wave tr...In order to solve the hole-filling mismatch problem in virtual view synthesis, a three-step repairing(TSR) algorithm was proposed. Firstly, the image with marked holes is decomposed by the non-subsampled shear wave transform(NSST), which will generate high-/low-frequency sub-images with different resolutions. Then the improved Criminisi algorithm was used to repair the texture information in the high-frequency sub-images, while the improved curvature driven diffusion(CDD) algorithm was used to repair the low-frequency sub-images with the image structure information. Finally, the repaired parts of high-frequency and low-frequency sub-images are synthesized to obtain the final image through inverse NSST. Experiments show that the peak signal-to-noise ratio(PSNR) of the TSR algorithm is improved by an average of 2-3 dB and 1-2 dB compared with the Criminisi algorithm and the nearest neighbor interpolation(NNI) algorithm, respectively.展开更多
基金The MSIP(Ministry of Science,ICT & Future Planning),Korea,under the ITRC(Information Technology Research Center)support program(NIPA-2013-H0301-13-2006)supervised by the NIPA(National IT Industry Promotion Agency)
文摘Depth image based rendering （DIBR） is an effective approach for virtual view synthesis in free viewpoint television and 3D video.One of the important steps in DIBR is filling the holes caused by disoeclusion regions and wrong depth values.Most of the existing hole-filling methods work well in areas of low spatial activity but fail to obtain satisfactory results in high spatial activity regions.In this paper,we combine the depth based hole-filling and the adaptive recursive interpolation algorithm which is capable of handling edges passing through the missing areas.Accoring to the experimental results,we confirm that the depth based adaptive recursive interpolation algorithm can provide better rendering quality objectively and subjectively.
基金supported by the National Natural Science Foundation of China (61834005, 61772417, 61602377, 61634004,61802304)the Shaanxi Province Key R&D Plan (2021GY-029)。
文摘In order to solve the hole-filling mismatch problem in virtual view synthesis, a three-step repairing(TSR) algorithm was proposed. Firstly, the image with marked holes is decomposed by the non-subsampled shear wave transform(NSST), which will generate high-/low-frequency sub-images with different resolutions. Then the improved Criminisi algorithm was used to repair the texture information in the high-frequency sub-images, while the improved curvature driven diffusion(CDD) algorithm was used to repair the low-frequency sub-images with the image structure information. Finally, the repaired parts of high-frequency and low-frequency sub-images are synthesized to obtain the final image through inverse NSST. Experiments show that the peak signal-to-noise ratio(PSNR) of the TSR algorithm is improved by an average of 2-3 dB and 1-2 dB compared with the Criminisi algorithm and the nearest neighbor interpolation(NNI) algorithm, respectively.
