Demosaicing of images obtained from single-chip imaging sensors in YUV color space
Pattern Recognition Letters
A new CFA interpolation framework
Signal Processing
Practical implementation of LMMSE demosaicing using luminance and chrominance spaces
Computer Vision and Image Understanding
PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras
IEEE Transactions on Image Processing
Digital zooming for color filter array-based image sensors
Real-Time Imaging
Region adaptive color demosaicing algorithm using color constancy
EURASIP Journal on Advances in Signal Processing
Demosaicking by alternating projections: theory and fast one-step implementation
IEEE Transactions on Image Processing
Selection of optimal spectral sensitivity functions for color filter arrays
IEEE Transactions on Image Processing
Color image demosaicking: An overview
Image Communication
Joint spatial-temporal color demosaicking
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
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Digital color cameras sample the continuous color spectrum using three or more filters; however, each pixel represents a sample of only one of the color bands. This arrangement is called a mosaic. To produce a full-resolution color image, the recorded image must be processed to estimate the values of the pixels for all the other color bands. This restoration process is often called demosaicking. This paper uses stacked notation to represent the mosaicked image capture and derives the minimum mean square error (MMSE) estimator for the demosaicked image. By making common assumptions, the restoration can be computed in a cost-effective manner. Extensions to the linear method are proposed to allow adaptive behavior