Mathematics for demosaicking

Author

Trussell, H.J. ; Hartwig, Robert E.

Author_Institution

Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA

Volume

11

Issue

4

fYear

2002

fDate

4/1/2002 12:00:00 AM

Firstpage

485

Lastpage

492

Abstract

Digital color cameras sample the continuous color spectrum using three or more filters; however, each pixel represents a sample of only one of the color bands. This arrangement is called a mosaic. To produce a full-resolution color image, the recorded image must be processed to estimate the values of the pixels for all the other color bands. This restoration process is often called demosaicking. This paper uses stacked notation to represent the mosaicked image capture and derives the minimum mean square error (MMSE) estimator for the demosaicked image. By making common assumptions, the restoration can be computed in a cost-effective manner. Extensions to the linear method are proposed to allow adaptive behavior

Keywords

adaptive signal processing; cameras; image colour analysis; image representation; image resolution; image restoration; image sampling; least mean squares methods; MMSE estimator; adaptive behavior; color bands; continuous color spectrum; demosaicking; digital color cameras; filters; full-resolution color image; image restoration; image sampling; linear method; mathematics; minimum mean square error; mosaicked image representation; pixel; recorded image; stacked notation; Bayesian methods; Color; Digital cameras; Image restoration; Image sampling; Mathematics; Optical filters; Optical sensors; Sampling methods; Sensor arrays;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2002.999681

Filename

999681