High quality color interpolation for color filter array with low complexity

Kwon Lee, Chulhee Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose fast color interpolation methods for color filter array (CFA). The proposed methods exploit correlations among the three color components. It has been reported that the quality of color interpolation can be significantly improved by utilizing correlation among color components. However, the complexity of such methods may increase significantly compared to those methods which separately interpolate each color component. On the other hand, the major application of CFA is portable imaging devices such as digital cameras or mobile phones. For portable devices, power consumption is an important issue. In this paper, we propose high quality color interpolation methods with reduced complexity. Experimental results show that the proposed methods provide noticeable improvements without significantly increasing the system complexity.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 13th International Multimedia Modeling Conference, MMM 2007, Proceedings
Pages314-322
Number of pages9
EditionPART 2
DOIs
Publication statusPublished - 2007 Dec 1
Event13th International Multimedia Modeling Conference, MMM 2007 - Singapore, Singapore
Duration: 2007 Jan 92007 Jan 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume4352 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Multimedia Modeling Conference, MMM 2007
CountrySingapore
CitySingapore
Period07/1/907/1/12

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lee, K., & Lee, C. (2007). High quality color interpolation for color filter array with low complexity. In Advances in Multimedia Modeling - 13th International Multimedia Modeling Conference, MMM 2007, Proceedings (PART 2 ed., pp. 314-322). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4352 LNCS, No. PART 2). https://doi.org/10.1007/978-3-540-69429-8_32