Color plane interpolation using alternating projections

By Bahadir K. Gunturk, Yucel Altunbasak, R. Mersereau. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002

738 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/e3870ed13c2a0c80d33dbbb8c58b16cdd9d694df

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In Computer Vision and Pattern Recognition

Citations in the corpus

High-quality linear interpolation for demosaicing of Bayer-patterned color images (2004, methodology): “For example, for interpolating the green channel in Laroche and Pres-cott’s method, the R and B channels are used to determine edge directions, which determine unequal weights to the terms in (1) for the green channel; the color differences R–”
Sparse Representation for Color Image Restoration (2008, background): “BI REFERS TO A SIMPLE BILINEAR INTERPOLATION, THEN, K, AP, OR, SA, CC REFER TO THE ALGORITHMS, RESPECTIVELY, FROM [51], [52], [53], [54], AND [59].”
Color filter array demosaicking: new method and performance measures (2003, methodology): “In [15], Gunturk et al. have recently proposed an effective scheme to exploit spectral correlation by alternately projecting the estimates of the missing color values onto constraint sets based on original CFA samples and prior knowledge of spectral correlation.”
Color demosaicking by local directional interpolation and nonlocal adaptive thresholding (2011, background): “Various CDM algorithms [3-18] have been proposed in the past decades.”
Color demosaicking via directional linear minimum mean square-error estimation (2005, methodology): “[9], which are among the best schemes.”
Multiframe demosaicing and super-resolution of color images (2006, background): “Note that many commercial digital video cameras can only be used in lower spatial resolution modes while working in higher frame rates.”
Exposing digital forgeries in color filter array interpolated images (2005, methodology): “…and propose a method that quantifies and detects them in any portion of an image.2 We show the general effectiveness of this technique in detecting traces of digital tampering and analyze its sensitivity and robustness to simple image distortions (compression, noise, and gamma correction).”
Adaptive homogeneity-directed demosaicing algorithm (2003, methodology): “Interpolation artifacts are reduced using techniques similar to the iterative algorithms proposed by [3][7][ 9 ].”
Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm (2005, neutral): “All these methods require considerable A u t h o r ' s p e r s o n a l”