An innovative computer program brings color
to grayscale images
Creating
a high-quality realistic color image from a grayscale picture can be
challenging. Conventional methods typically require the user’s input, either by
using a scribbling tool to color the image manually or by using a color
transfer. Both options can result in poor colorization quality limited by the
user’s degree of skill or the range of reference images available.
Alex
Yong-Sang Chia at the A*STAR’s Institute for Infocomm Research and co-workers1
have now developed a computer program that utilizes the vast amount of imagery
available on the internet to find suitable color matches for grayscale images.
The program searches hundreds of thousands of online color images, cross-referencing
their key features and objects in the foreground with those of grayscale
pictures.
“We
have developed a method that takes advantage of the plentiful supply of
internet data to colorize gray photos,” Chia explains. “The user segments the
image into separate major foreground objects and adds semantic labels naming
these objects in the gray photo. Our program then scans the internet using
these inputs for suitable object color matches.”
Given
the vast amount of visual data available online, not all of the chosen images
are useful. Once the initial color images have been found, the program then
filters them to find the most realistic and suitable matches for the grayscale
object inputs.
“Our
method automatically detects and segments salient objects from an internet
photo,” explains Chia. “It then exploits shape and appearance information of
these objects to compute its relevance to the original grayscale image data.”
The
grayscale image is then automatically colored using the information collected
from internet-based images (pictured). Plausible colorization of images is
vitally important, however, as the human eye can quickly distinguish between
real and ‘false’ coloring. To this end, the user has the final say over the
choice of colors. “The program generates several image colorizations and the
user can pick the one that fits best from a graphical user interface,” explains
Chia.
To
demonstrate the capability of the program, Chia and his team showed a group of
people their colored grayscale images alongside real color pictures, asking
them to identify which ones had been colored artificially. “Our colored images
were classed as ‘real’ up to 65% of the time,” says Chia. “Overall the
colorization results are visually pleasing and perceptually meaningful to
users.”
The
researchers hope to expand the range of applications using this technology in
the future. They envision that the technology may one day become so powerful that
it could be used to generate realistic animations.
The
A*STAR-affiliated researchers contributing to this research are from the Institute for Infocomm Research
References
- Chia, A. Y. S. et al. Semantic colorization with internet
images. ACM Transactions on Graphics (TOG) - Proceedings of ACM
SIGGRAPH Asia 2011 30, 156 (2012). | article
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