logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

Color image resolution conversion

delete2005-03-01
delete8
PRE
AI
M
M. J. Vrhel
DOI：10.1109/TIP.2004.841194delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
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:
INTERPOLATION
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

Organization

No organization information available