TY - GEN
T1 - A Spatial-Focal Error Concealment Scheme for Corrupted Focal Stack Video
AU - Wu, Kejun
AU - Wang, Yi
AU - Liu, Wenyang
AU - Yap, Kim Hui
AU - Chau, Lap Pui
N1 - Funding Information:
This research / project is supported by the National Research Foundation, Singapore, and Cyber Security Agency of Singapore under its National Cybersecurity R&D Programme (NRF2018NCR-NCR009-0001). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore and Cyber Security Agency of Singapore.
Publisher Copyright:
© 2023 IEEE.
PY - 2023/5
Y1 - 2023/5
N2 - Focal stack image sequences can be regarded as successive frames of videos, which are densely captured by focusing on a stack of focal planes. This type of data is able to provide focus cues for display technologies. Before the displays on the user side, focal stack video is possibly corrupted during compression, storage and transmission chains, generating error frames on the decoder side. The error regions are difficult to be recovered due to the focal changes among frames. Conventional error concealment methods result in sharpness inconsistency between recovered regions and their spatial adjacent regions. Motivated by this, in this paper, we propose a spatial-focal error concealment scheme specialized for focal stack videos. The spatial adjacent regions around an error region are employed to reveal the prediction relations between error frame and focal adjacent frames. Gaussian blur filtering and Lucy-Richardson deblur filtering are applied to simulate the video focal changes. In this way, the error regions can be well recovered by exploiting the spatial-focal information. Experiment results show that the proposed scheme can achieve the highest objective quality in terms of PSNR and SSIM. It can also obtain the best subjective quality with sharpness consistency in recovered regions and without block effect.
AB - Focal stack image sequences can be regarded as successive frames of videos, which are densely captured by focusing on a stack of focal planes. This type of data is able to provide focus cues for display technologies. Before the displays on the user side, focal stack video is possibly corrupted during compression, storage and transmission chains, generating error frames on the decoder side. The error regions are difficult to be recovered due to the focal changes among frames. Conventional error concealment methods result in sharpness inconsistency between recovered regions and their spatial adjacent regions. Motivated by this, in this paper, we propose a spatial-focal error concealment scheme specialized for focal stack videos. The spatial adjacent regions around an error region are employed to reveal the prediction relations between error frame and focal adjacent frames. Gaussian blur filtering and Lucy-Richardson deblur filtering are applied to simulate the video focal changes. In this way, the error regions can be well recovered by exploiting the spatial-focal information. Experiment results show that the proposed scheme can achieve the highest objective quality in terms of PSNR and SSIM. It can also obtain the best subjective quality with sharpness consistency in recovered regions and without block effect.
UR - http://www.scopus.com/inward/record.url?scp=85160720272&partnerID=8YFLogxK
U2 - 10.1109/DCC55655.2023.00017
DO - 10.1109/DCC55655.2023.00017
M3 - Conference article published in proceeding or book
AN - SCOPUS:85160720272
T3 - Data Compression Conference Proceedings
SP - 91
EP - 100
BT - Proceedings - DCC 2023
A2 - Bilgin, Ali
A2 - Marcellin, Michael W.
A2 - Serra-Sagrista, Joan
A2 - Storer, James A.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 Data Compression Conference, DCC 2023
Y2 - 21 March 2023 through 24 March 2023
ER -