Multiscale Shape and Detail Enhancement from Multi-light Image Collections
ACM Transactions on Graphics (Proc. SIGGRAPH), August 2007
Abstract
We present a new image-based technique for enhancing the shape
and surface details of an object. The input to our system is a small
set of photographs taken from a fixed viewpoint, but under varying
lighting conditions. For each image we compute a multiscale decomposition
based on the bilateral filter and then reconstruct an enhanced
image that combines detail information at each scale across
all the input images. Our approach does not require any information
about light source positions, or camera calibration, and can
produce good results with 3 to 5 input images. In addition our system
provides a few high-level parameters for controlling the amount
of enhancement and does not require pixel-level user input. We
show that the bilateral filter is a good choice for our multiscale algorithm
because it avoids the halo artifacts commonly associated
with the traditional Laplacian image pyramid. We also develop a
new scheme for computing our multiscale bilateral decomposition
that is simple to implement, fast O(N2 log N) and accurate.
Paper
Citation
Raanan Fattal, Maneesh Agrawala, and Szymon Rusinkiewicz.
"Multiscale Shape and Detail Enhancement from Multi-light Image Collections."
ACM Transactions on Graphics (Proc. SIGGRAPH) 26(3), August 2007.
BibTeX
@article{Fattal:2007:MSA, author = "Raanan Fattal and Maneesh Agrawala and Szymon Rusinkiewicz", title = "Multiscale Shape and Detail Enhancement from Multi-light Image Collections", journal = "ACM Transactions on Graphics (Proc. SIGGRAPH)", year = "2007", month = aug, volume = "26", number = "3" }