Practical implementation of LMMSE demosaicing using luminance and chrominance spaces
Computer Vision and Image Understanding
Color Demosaicing Using Asymmetric Directional Interpolation and Hue Vector Smoothing
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Additive spread-spectrum watermark detection in demosaicked images
Proceedings of the 11th ACM workshop on Multimedia and security
Regularization approaches to demosaicking
IEEE Transactions on Image Processing
Demosaicing based on the correlations between low-resolution images
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Color filter array demosaicking using joint bilateral filter
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
LMMSE frequency merging for demosaicking
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Robust color demosaicking with adaptation to varying spectral correlations
IEEE Transactions on Image Processing
Adaptive color filter array demosaicking based on constant hue and local properties of luminance
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
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
Joint color decrosstalk and demosaicking for CFA cameras
IEEE Transactions on Image Processing
Color kernel regression for robust direct upsampling from raw data of general color filter array
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Edge adaptive color demosaicking based on the spatial correlation of the bayer color difference
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
Color image demosaicking: An overview
Image Communication
Novel color demosaicking for noisy color filter array data
Signal Processing
Effective demosaicking algorithm based on edge property for color filter arrays
Digital Signal Processing
Joint spatial-temporal color demosaicking
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
On a generalized demosaicking procedure: a taxonomy of single-sensor imaging solutions
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Color demosaicking with an image formation model and adaptive PCA
Journal of Visual Communication and Image Representation
Hi-index | 0.01 |
Color mosaic sampling schemes are widely used in digital cameras. Given the resolution of CCD sensor arrays, the image quality of digital cameras using mosaic sampling largely depends on the performance of the color demosaicking process. A common problem with existing color demosaicking algorithms is an inconsistency of sample interpolations in different primary color channels, which is the cause of the most objectionable color artifacts. To cure the problem, we propose a new primary-consistent soft-decision framework (PCSD) of color demosaicking. In the PCSD framework, we make multiple estimates of a missing color sample under different hypotheses on edge or texture directions. The estimates are made via a primary consistent interpolation, meaning that all three primary components of a color are interpolated in the same direction. The final estimate of a color sample is obtained by testing different interpolation hypotheses in the reconstructed full-resolution color image and selecting the best via an optimal statistical decision or inference process. A concrete color demosaicking method of the PCSD framework is presented. This new method eliminates certain types of color artifacts of existing color demosaicking methods. Extensive experimental results demonstrate that the PCSD approach can significantly improve the image quality of digital cameras in both subjective and objective measures. In some instances, our gain over the competing methods can be as much as 7dB.