TY - GEN
T1 - Optimized inter-view prediction based light field image compression with adaptive reconstruction
AU - Jia, Chuanmin
AU - Yang, Yekang
AU - Zhang, Xinfeng
AU - Zhang, Xiang
AU - Wang, Shiqi
AU - Wang, Shanshe
AU - Ma, Siwei
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - In this paper, we explore the structure of light field (LF) and efficiently improve the performance of the pseudo sequence based lenslet image compression, by optimized sub-view rearrangement, enhanced illumination compensation and adaptive reconstruction filtering. First, the decomposed sub-view images are rearranged into a pseudo sequence according to our optimized scan order based on sub-view correlation. Second, the generated pseudo sequence is compressed with JEM codec in which we enhance the illumination compensation by adaptively selecting reference pixels used in parameter derivation. Finally, to reduce the distortions in lenslet image decomposition and reconstruction, we propose an lenslet reconstruction method by applying adaptive filters to the reconstructed lenslet images to compensate the reconstruction errors. Each filter is derived by minimizing the distortions between the original and reconstructed pixels with same geolocation in the lenslet image. Extensive experimental results show that the proposed method achieves up to 53.7% bit rate reduction over HEVC intra coding and 34.8% over JEM intra coding in terms of BDBR.
AB - In this paper, we explore the structure of light field (LF) and efficiently improve the performance of the pseudo sequence based lenslet image compression, by optimized sub-view rearrangement, enhanced illumination compensation and adaptive reconstruction filtering. First, the decomposed sub-view images are rearranged into a pseudo sequence according to our optimized scan order based on sub-view correlation. Second, the generated pseudo sequence is compressed with JEM codec in which we enhance the illumination compensation by adaptively selecting reference pixels used in parameter derivation. Finally, to reduce the distortions in lenslet image decomposition and reconstruction, we propose an lenslet reconstruction method by applying adaptive filters to the reconstructed lenslet images to compensate the reconstruction errors. Each filter is derived by minimizing the distortions between the original and reconstructed pixels with same geolocation in the lenslet image. Extensive experimental results show that the proposed method achieves up to 53.7% bit rate reduction over HEVC intra coding and 34.8% over JEM intra coding in terms of BDBR.
KW - Adaptive Filter
KW - Compression
KW - Enhanced Illuminance Compensation
KW - Lenslet Image
KW - Reorder
UR - https://www.scopus.com/pages/publications/85045293059
U2 - 10.1109/ICIP.2017.8297148
DO - 10.1109/ICIP.2017.8297148
M3 - 会议稿件
AN - SCOPUS:85045293059
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 4572
EP - 4576
BT - 2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
PB - IEEE Computer Society
T2 - 24th IEEE International Conference on Image Processing, ICIP 2017
Y2 - 17 September 2017 through 20 September 2017
ER -