Color image resolution conversion

Author

Vrhel, Michael

Author_Institution

ViewAhead Technol., Redmond, WA, USA

Volume

14

Issue

3

fYear

2005

fDate

3/1/2005 12:00:00 AM

Firstpage

328

Lastpage

333

Abstract

In this paper, we look at the problem of spatially scaling color images. We focus on an approach that takes advantage of the human visual system´s color spatial frequency sensitivity. The algorithm performs an efficient least-squares (LS) resolution conversion for the luminance channel and a low-complexity pixel replication/reduction in the chrominance channels. The performance of the algorithm is compared to a LS method in sRGB and CIELAB color spaces, as well as standard bilinear interpolation in sRGB space. The comparisons are made in terms of computational cost and color error in sCIELAB.

Keywords

computational complexity; image colour analysis; image resolution; interpolation; least squares approximations; bilinear interpolation; color image resolution conversion; computational complexity; least-squares resolution conversion; luminance channel; spatial frequency sensitivity; Color; Colored noise; Computational efficiency; Embedded system; Humans; Image converters; Image resolution; Interpolation; Spatial resolution; Transform coding; Algorithms; Artificial Intelligence; Color; Colorimetry; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2004.841194

Filename

1395988