Color demosaicking using deinterlacing and median-based filtering techniques

Wen-Tsung Huang; Wen-Jan Chen; Shen-Chuan Tai

doi:10.1117/1.3517068

1 October 2010 Color demosaicking using deinterlacing and median-based filtering techniques

Wen-Tsung Huang, Wen-Jan Chen, Shen-Chuan Tai

Author Affiliations +

Journal of Electronic Imaging, Vol. 19, Issue 4, 043018 (October 2010). https://doi.org/10.1117/1.3517068

Abstract

Color demosaicking is critical to the image quality of single-sensor-based imaging devices. Caused by the sampling pattern of color filter array (CFA), the demosaicked images typically suffer from visual color artifacts in regions of high frequency and sharp edge structures, degrading the quality of camera output. We present a new high-quality demosaicking algorithm by taking advantage of deinterlacing and median-based filtering techniques. We treat the sampled green data of Bayer CFA as a form of diagonal interlaced green planes and make use of some key concepts about spatial deinterlacing to help the edge estimation in terms of both various directions and accuracy. In addition, a specific edge feature, sharp line edge of width 1 pixel, can also be handed well by the proposed method. The median-based filtering techniques are developed for suppressing most visual demosaicking artifacts, such as zipper effect, false color artifact, and interpolation artifact. Experimental results show that our algorithm is effective in suppressing visual artifacts, preserving the edges of image with sharpness and satisfying visual inspection, while keeping computational efficiency.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Wen-Tsung Huang, Wen-Jan Chen, and Shen-Chuan Tai "Color demosaicking using deinterlacing and median-based filtering techniques," Journal of Electronic Imaging 19(4), 043018 (1 October 2010). https://doi.org/10.1117/1.3517068

Published: 1 October 2010

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available