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.
|Title of host publication||Image Analysis and Recognition - 11th International Conference, ICIAR 2014, Proceedings|
|Editors||Mohamed Kamel, Aurélio Campilho|
|Number of pages||9|
|Publication status||Published - 2014|
|Event||11th International Conference on Image Analysis and Recognition, ICIAR 2014 - Vilamoura, Portugal|
Duration: 2014 Oct 22 → 2014 Oct 24
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||11th International Conference on Image Analysis and Recognition, ICIAR 2014|
|Period||14/10/22 → 14/10/24|
Bibliographical notePublisher Copyright:
© Springer International Publishing Switzerland 2014.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)