Paper Info
Title
Saliency Driven Black Point Compensation
Abstract
We present a novel framework for automatically determining whether or not to apply black point compensation (BPC) in image reproduction. Visually salient objects have a larger influence on determining image quality than the number of dark pixels in an image, and thus should drive the use of BPC. We propose a simple and efficient algorithmic implementation to determine when to apply BPC based on low-level saliency estimation. We evaluate our algorithm with a psychophysical experiment on an image data set printed with or without BPC on a Canon printer. We find that our algorithm is correctly able to predict the observers' preferences in all cases when the saliency maps are unambiguous and accurate.
Year
DOI
Venue
2011
10.1117/12.872448
COLOR IMAGING XVI: DISPLAYING, PROCESSING, HARDCOPY, AND APPLICATIONS
Keywords
Field
DocType
black point compensation, saliency, color re-rendering, ICC, gamut mapping
Computer vision,Salience (neuroscience),Salient objects,Image quality,Pixel,Artificial intelligence,Image reproduction,Physics
Conference
Volume
ISSN
Citations 
7866
0277-786X
0
PageRank 
References 
Authors
0.34
6
3
Name
Order
Citations
PageRank
Albrecht Lindner1202.63
Nicolas Bonnier2839.52
Sabine Süsstrunk34984207.02