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

doi:10.1155/2010/874364

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

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

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 language	English
Article number	874364
Journal	Eurasip Journal on Image and Video Processing
Volume	2010
DOIs	https://doi.org/10.1155/2010/874364
Publication status	Published - 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

Access to Document

10.1155/2010/874364

Cite this

@article{fea27d2d785b46db8b46ef90ab502830,

title = "Edge adaptive color demosaicking based on the spatial correlation of the bayer color difference",

abstract = "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.",

author = "Kang, {Moon Gi} and Oh, {Hyun Mook} and Kim, {Chang Won} and Han, {Young Seok}",

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)).",

year = "2010",

doi = "10.1155/2010/874364",

language = "English",

volume = "2010",

journal = "Eurasip Journal on Image and Video Processing",

issn = "1687-5176",

publisher = "Springer Publishing Company",

}

TY - JOUR

T1 - Edge adaptive color demosaicking based on the spatial correlation of the bayer color difference

AU - Kang, Moon Gi

AU - Oh, Hyun Mook

AU - Kim, Chang Won

AU - Han, Young Seok

N1 - 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)).

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=78650757857&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78650757857&partnerID=8YFLogxK

U2 - 10.1155/2010/874364

DO - 10.1155/2010/874364

M3 - Article

AN - SCOPUS:78650757857

SN - 1687-5176

VL - 2010

JO - Eurasip Journal on Image and Video Processing

JF - Eurasip Journal on Image and Video Processing

M1 - 874364

ER -

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

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this