Restoring subsampled color images
Machine Vision and Applications
Digital Color Imaging Handbook
Digital Color Imaging Handbook
A Multi-Spectral Image Database and Its Application to Image Rendering across Illumination
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Color filter arrays: design and performance analysis
IEEE Transactions on Consumer Electronics
Optimization of sensor response functions for colorimetry of reflective and emissive objects
IEEE Transactions on Image Processing
Mathematical methods for the design of color scanning filters
IEEE Transactions on Image Processing
Mathematical methods for the analysis of color scanning filters
IEEE Transactions on Image Processing
Figures of merit for color scanners
IEEE Transactions on Image Processing
Optimal nonnegative color scanning filters
IEEE Transactions on Image Processing
Demosaicing: image reconstruction from color CCD samples
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Color plane interpolation using alternating projections
IEEE Transactions on Image Processing
A subspace matching color filter design methodology for a multispectral imaging system
IEEE Transactions on Image Processing
Spatio-Spectral Color Filter Array Design for Optimal Image Recovery
IEEE Transactions on Image Processing
Optimal color filters in the presence of noise
IEEE Transactions on Image Processing
Novel color demosaicking for noisy color filter array data
Signal Processing
Computational plenoptic imaging
ACM SIGGRAPH 2012 Courses
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A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ΔE error metric and a qualitative assessment.