Title :
Adaptive homogeneity-directed demosaicing algorithm
Author :
Hirakawa, Keigo ; Parks, Thomas W.
Author_Institution :
Cornell Univ., Ithaca, NY, USA
fDate :
3/1/2005 12:00:00 AM
Abstract :
A cost-effective digital camera uses a single-image sensor, applying alternating patterns of red, green, and blue color filters to each pixel location. A way to reconstruct a full three-color representation of color images by estimating the missing pixel components in each color plane is called a demosaicing algorithm. This paper presents three inherent problems often associated with demosaicing algorithms that incorporate two-dimensional (2-D) directional interpolation: misguidance color artifacts, interpolation color artifacts, and aliasing. The level of misguidance color artifacts present in two images can be compared using metric neighborhood modeling. The proposed demosaicing algorithm estimates missing pixels by interpolating in the direction with fewer color artifacts. The aliasing problem is addressed by applying filterbank techniques to 2-D directional interpolation. The interpolation artifacts are reduced using a nonlinear iterative procedure. Experimental results using digital images confirm the effectiveness of this approach.
Keywords :
cameras; channel bank filters; image colour analysis; image reconstruction; image representation; image segmentation; interpolation; adaptive homogeneity-directed demosaicing algorithm; color artifact; digital camera; directional interpolation; filterbank technique; image reconstruction; metric neighborhood modeling; nonlinear iterative procedure; three-color image representation; Color; Digital cameras; Digital filters; Digital images; Filter bank; Image reconstruction; Interpolation; Iterative algorithms; Pixel; Two dimensional displays; Color artifact; demosaicing algorithm; digital camera; filterbank; interpolation; metric neighborhood model; Algorithms; Artifacts; Artificial Intelligence; Color; Colorimetry; Computer Graphics; Data Compression; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2004.838691