TY - GEN
T1 - Compression for multiple reconstructions
AU - Dar, Yehuda
AU - Elad, Michael
AU - Bruckstein, Alfred M.
N1 - Funding Information:
This research was supported in part by the European Research Council under European Unions Seventh Framework Program, ERC Grant agreement no. 320649, and by the Israel Science Foundation grant no. 2597/16.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/29
Y1 - 2018/8/29
N2 - In this work we propose a method for optimizing the lossy compression for a network of diverse reconstruction systems. We focus on adapting a standard image compression method to a set of candidate displays, presenting the decompressed signals to viewers. Each display is modeled as a linear operator applied after decompression, and its probability to serve a network user. We formulate a complicated operational ratedistortion optimization trading-off the network's expected mean-squared reconstruction error and the compression bit-cost. Using the alternating direction method of multipliers (ADMM) we develop an iterative procedure where the network structure is separated from the compression method, enabling the reliance on standard compression techniques. We present experimental results showing our method to be the best approach for adjusting high bit-rate image compression (using the state-of-the-art HEVC standard) to a set of displays modeled as blur degradations.
AB - In this work we propose a method for optimizing the lossy compression for a network of diverse reconstruction systems. We focus on adapting a standard image compression method to a set of candidate displays, presenting the decompressed signals to viewers. Each display is modeled as a linear operator applied after decompression, and its probability to serve a network user. We formulate a complicated operational ratedistortion optimization trading-off the network's expected mean-squared reconstruction error and the compression bit-cost. Using the alternating direction method of multipliers (ADMM) we develop an iterative procedure where the network structure is separated from the compression method, enabling the reliance on standard compression techniques. We present experimental results showing our method to be the best approach for adjusting high bit-rate image compression (using the state-of-the-art HEVC standard) to a set of displays modeled as blur degradations.
KW - Alternating direction method of multipliers (ADMM)
KW - Image compression
KW - Image deblurring
KW - Rate-distortion optimization
KW - Signal compression
UR - http://www.scopus.com/inward/record.url?scp=85062898165&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2018.8451743
DO - 10.1109/ICIP.2018.8451743
M3 - Conference contribution
AN - SCOPUS:85062898165
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 440
EP - 444
BT - 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
PB - IEEE Computer Society
T2 - 25th IEEE International Conference on Image Processing, ICIP 2018
Y2 - 7 October 2018 through 10 October 2018
ER -