Title :
Color image resolution conversion
Author_Institution :
ViewAhead Technol., Redmond, WA, USA
fDate :
3/1/2005 12:00:00 AM
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;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2004.841194