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 journalArticle

7 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 languageEnglish
Article number874364
JournalEurasip Journal on Image and Video Processing
Volume2010
DOIs
Publication statusPublished - 2010 Dec 1

Fingerprint

Color
Image quality

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Electrical and Electronic Engineering

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}",
year = "2010",
month = "12",
day = "1",
doi = "10.1155/2010/874364",
language = "English",
volume = "2010",
journal = "Eurasip Journal on Image and Video Processing",
issn = "1687-5176",
publisher = "Springer Publishing Company",

}

Edge adaptive color demosaicking based on the spatial correlation of the bayer color difference. / Kang, Moon Gi; Oh, Hyun Mook; Kim, Chang Won; Han, Young Seok.

In: Eurasip Journal on Image and Video Processing, Vol. 2010, 874364, 01.12.2010.

Research output: Contribution to journalArticle

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

PY - 2010/12/1

Y1 - 2010/12/1

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

VL - 2010

JO - Eurasip Journal on Image and Video Processing

JF - Eurasip Journal on Image and Video Processing

SN - 1687-5176

M1 - 874364

ER -