By Topic

A Colorization Method Based on Fuzzy Clustering and Distance Transformation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
ZhaoHui Zhang ; Coll. of Math. & Inf. Sci., Hebei Normal Univ., Shijiazhuang, China ; HuiQing Cui ; Hanqing Lu ; RuiQing Chen
more authors

This paper proposes a novel colorization algorithm for monochrome still images based on fuzzy clustering and distance transformation. Given small amount of typical color scribbles manually marked on the input grayscale image, the followed colorization process consists of four main steps: color scribble extraction, distance transformation and spatial weight estimation, fuzzy clustering and luminance weight estimation, and weighted color blending. By propagating the local color hints from the given scribbles to the whole grayscale image, the final output color image can be produced. Experimental results show that when the content of grayscale image is relatively simple, the proposed colorization method can efficiently gain a good colorized image with only a small number of scribbles. The algorithm is simple and easy to implement. Moreover, it takes only several seconds to complete the colorization process but can get visually vivid result.

Published in:

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Date of Conference:

17-19 Oct. 2009