Demosaicing With Directional Filtering and a posteriori Decision

Most digital cameras use a color filter array to capture the colors of the scene. Downsampled versions of the red, green, and blue components are acquired, and an interpolation of the three colors is necessary to reconstruct a full representation of the image. This color interpolation is known as de...

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Bibliographic Details
Published in:IEEE transactions on image processing 2007-01, Vol.16 (1), p.132-141
Main Authors: Menon, D., Andriani, S., Calvagno, G.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Arrays
Bayer pattern
Color
color filter array (CFA) interpolation
Colorimetry - methods
Computational efficiency
Computer Graphics
demosaicing
Detection, estimation, filtering, equalization, prediction
Digital cameras
Digital filters
directional filtering
Exact sciences and technology
Filtering
Filtration
Frequency
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Image reconstruction
Information Storage and Retrieval - methods
Information, signal and communications theory
Interpolation
Layout
Numerical Analysis, Computer-Assisted
Reconstruction algorithms
Representations
Sensor arrays
Signal and communications theory
Signal processing
Signal Processing, Computer-Assisted
Signal representation. Spectral analysis
Signal, noise
Telecommunications and information theory
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Description
Summary:Most digital cameras use a color filter array to capture the colors of the scene. Downsampled versions of the red, green, and blue components are acquired, and an interpolation of the three colors is necessary to reconstruct a full representation of the image. This color interpolation is known as demosaicing. The most effective demosaicing techniques proposed in the literature are based on directional filtering and a posteriori decision. In this paper, we present a novel approach to this reconstruction method. A refining step is included to further improve the resulting reconstructed image. The proposed approach requires a limited computational cost and gives good performance even when compared to more demanding techniques
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2006.884928