TY - GEN
T1 - Sparsifying orthogonal transforms with compact bases for data compression
AU - Hou, Junhui
AU - Liu, Hui
AU - Chau, Lap Pui
AU - He, Ying
AU - Chen, Jie
N1 - Publisher Copyright:
© 2016 Asia Pacific Signal and Information Processing Association.
PY - 2017/1/17
Y1 - 2017/1/17
N2 - Learned Sparsifying orthogonal transforms (SOTs) have proven to be a powerful tool for image and video processing. In this paper, we propose a variant of SOT, named compact bases SOT, or CB-SOT, which has several promising features for data compression: (i) as an input-adaptive transform, it can sparsely represent the input data very well; (ii) the transform matrix is orthogonal; (iii) unlike SOT, the transform matrix is compact, since a large amount of entries are zero. We formulate CB-SOT as a constrained optimization problem and solve it efficiently using alternating iteration. Experiments on images show that the proposed algorithm empirically converges well and CB-SOT produces better performance of energy compaction, indicating its potential for data compression.
AB - Learned Sparsifying orthogonal transforms (SOTs) have proven to be a powerful tool for image and video processing. In this paper, we propose a variant of SOT, named compact bases SOT, or CB-SOT, which has several promising features for data compression: (i) as an input-adaptive transform, it can sparsely represent the input data very well; (ii) the transform matrix is orthogonal; (iii) unlike SOT, the transform matrix is compact, since a large amount of entries are zero. We formulate CB-SOT as a constrained optimization problem and solve it efficiently using alternating iteration. Experiments on images show that the proposed algorithm empirically converges well and CB-SOT produces better performance of energy compaction, indicating its potential for data compression.
KW - image compression
KW - Nonlinear approximation
KW - optimization
KW - orthogonal transform
KW - sparse representation
UR - http://www.scopus.com/inward/record.url?scp=85013809585&partnerID=8YFLogxK
U2 - 10.1109/APSIPA.2016.7820905
DO - 10.1109/APSIPA.2016.7820905
M3 - Conference article published in proceeding or book
AN - SCOPUS:85013809585
T3 - 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
BT - 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
Y2 - 13 December 2016 through 16 December 2016
ER -