.png){kind=icon}
.png){kind=icon}
Return
A new CFA interpolation framework
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sigpro.2005.09.005.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The paper introduces a new color filter array (CFA) interpolation method for digital still cameras. The proposed interpolation scheme is able to (i) overcome the hardware limitations of existing CFA based image acquisition solutions, and (ii) restore color images with excellent visual quality. The scheme employs an adaptive edge-sensing mechanism which operates along the vertical, horizontal and diagonal directions to correctly interpolate unavailable color components. Building on the computed edge-sensing map and a refined color-difference model, a new correlation-correction algorithm is introduced. In addition to the basic model, adaptively determined correction operations are also discussed and analyzed. The solutions proposed here, described in a novel vector notation, constitute a unique CFA interpolation framework, which readily unifies previous, seemingly unrelated, results. Simulation studies indicate that the proposed method is computationally efficient and yields excellent performance, in terms of subjective and objective image quality measures, while outperforming state-of-the-art CFA interpolation methods. (C) 2005 Elsevier B.V. All rights reserved.
Keywords:
digital camera
color filter array
Bayer pattern
demosaicing
image restoration
color interpolation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.9K
Citations:
1.7W
Organization
No organization information available