Sparsifying orthogonal transforms with compact bases for data compression

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

1 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Title of host publication2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9789881476821
Publication statusPublished - Dec 2016
Externally publishedYes

Conference

Title2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
PlaceKorea, Republic of
CityJeju
Period13 - 16 December 2016

Abstract

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.

Research Area(s)

  • image compression, Nonlinear approximation, optimization, orthogonal transform, sparse representation

Citation Format(s)

Sparsifying orthogonal transforms with compact bases for data compression. / Hou, Junhui; Liu, Hui; Chau, Lap-Pui; He, Ying; Chen, Jie.

2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7820905.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review