Effective use of spatial and spectral correlations for color filter array demosaicking
IEEE Transactions on Consumer Electronics
Demosaicing: image reconstruction from color CCD samples
IEEE Transactions on Image Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Color plane interpolation using alternating projections
IEEE Transactions on Image Processing
Color filter array demosaicking: new method and performance measures
IEEE Transactions on Image Processing
Primary-consistent soft-decision color demosaicking for digital cameras (patent pending)
IEEE Transactions on Image Processing
Demosaicing by successive approximation
IEEE Transactions on Image Processing
Linear demosaicing inspired by the human visual system
IEEE Transactions on Image Processing
Effective color interpolation in CCD color filter arrays using signal correlation
IEEE Transactions on Circuits and Systems for Video Technology
The eISP low-power and tiny silicon footprint programmable video architecture
Journal of Real-Time Image Processing
Hi-index | 0.00 |
Most commercial digital cameras use a single electronic sensor overlaid with a color filter array (CFA) to capture imagery. Since only one primary color is sampled in each pixel, the missing color primaries must be reconstructed by interpolation. In this paper, an adaptive demosaicking scheme for CFA interpolation is proposed. The scheme uses intra-channel correlation, color difference correlation, constant hue, and luminance-color difference correlation is proposed. A rough interpolation is first implemented by bilinear interpolation. Then the color difference correlation and constant hue are successively used to update the missing color primaries. To obtain high quality color images, an adaptive algorithm using luminance-color difference correlation and the information of edge direction is iteratively applied to improve the image quality around the edges. Simulation results demonstrate that the image quality of the proposed algorithm is better than that of the approach using color difference correlation in terms of peak signal-to-noise ratio (PSNR).