Edge adaptive color demosaicking based on the spatial correlation of the bayer color difference

Moon Gi Kang, Hyun Mook Oh, Chang Won Kim, Young Seok Han

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


An edge adaptive color demosaicking algorithm that classifies the region types and estimates the edge direction on the Bayer color filter array (CFA) samples is proposed. In the proposed method, the optimal edge direction is estimated based on the spatial correlation on the Bayer color difference plane, which adopts the local directional correlation of an edge region of the Bayer CFA samples. To improve the image quality with the consistent edge direction, we classify the region of an image into three different types, such as edge, edge pattern, and flat regions. Based on the region types, the proposed method estimates the edge direction adaptive to the regions. As a result, the proposed method reconstructs clear edges with reduced visual distortions in the edge and the edge pattern regions. Experimental results show that the proposed method outperforms conventional edge-directed methods on objective and subjective criteria.

Original languageEnglish
Article number874364
JournalEurasip Journal on Image and Video Processing
Publication statusPublished - 2010

Bibliographical note

Funding Information:
This research was supported by Mid-career Researcher Program through the NRF(National Research Foundation of Korea) grant funded by the MEST (no. 2010-0000345) and by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2010-( C1090-1011-0003)).

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Electrical and Electronic Engineering


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