Abstract
Colorization based coding is a technique which compresses a color image using the colorization method. The main issue in colorization based coding is to extract a good RP(representative pixel) set from the original color image from which the colored image can be reconstructed in the decoder to a sufficient level. In this paper, we propose an iterative sparse coding method for the extraction of the RP set. Observations show that the proposed method computes simultaneously the locally optimal RP set and the locally optimal Levin’s colorization matrix. Furthermore, experimental results show that the proposed method provides better color image reconstruction and compression rate than conventional colorization based coding methods.
| Original language | English |
|---|---|
| Title of host publication | Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings |
| Editors | Mohamed Kamel, Aurélio Campilho |
| Publisher | Springer Verlag |
| Pages | 112-120 |
| Number of pages | 9 |
| ISBN (Electronic) | 9783319117577 |
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
| Event | 11th International Conference on Image Analysis and Recognition, ICIAR 2014 - Vilamoura, Portugal Duration: 2014 Oct 22 → 2014 Oct 24 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 8814 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 11th International Conference on Image Analysis and Recognition, ICIAR 2014 |
|---|---|
| Country | Portugal |
| City | Vilamoura |
| Period | 14/10/22 → 14/10/24 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Iterative sparse coding for colorization based compression. / Lee, Suk Ho; Oh, Paul; Kang, Moon Gi.
Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings. ed. / Mohamed Kamel; Aurélio Campilho. Springer Verlag, 2014. p. 112-120 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8814).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Iterative sparse coding for colorization based compression
AU - Lee, Suk Ho
AU - Oh, Paul
AU - Kang, Moon Gi
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Colorization based coding is a technique which compresses a color image using the colorization method. The main issue in colorization based coding is to extract a good RP(representative pixel) set from the original color image from which the colored image can be reconstructed in the decoder to a sufficient level. In this paper, we propose an iterative sparse coding method for the extraction of the RP set. Observations show that the proposed method computes simultaneously the locally optimal RP set and the locally optimal Levin’s colorization matrix. Furthermore, experimental results show that the proposed method provides better color image reconstruction and compression rate than conventional colorization based coding methods.
AB - Colorization based coding is a technique which compresses a color image using the colorization method. The main issue in colorization based coding is to extract a good RP(representative pixel) set from the original color image from which the colored image can be reconstructed in the decoder to a sufficient level. In this paper, we propose an iterative sparse coding method for the extraction of the RP set. Observations show that the proposed method computes simultaneously the locally optimal RP set and the locally optimal Levin’s colorization matrix. Furthermore, experimental results show that the proposed method provides better color image reconstruction and compression rate than conventional colorization based coding methods.
UR - http://www.scopus.com/inward/record.url?scp=84908670834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84908670834&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11758-4_13
DO - 10.1007/978-3-319-11758-4_13
M3 - Conference contribution
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 112
EP - 120
BT - Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings
A2 - Kamel, Mohamed
A2 - Campilho, Aurélio
PB - Springer Verlag
ER -