纳金网
标题:
Non-Local Image Reconstruction for Efficient BTF Synthesis
[打印本页]
作者:
彬彬
时间:
2012-1-5 08:44
标题:
Non-Local Image Reconstruction for Efficient BTF Synthesis
1 Introduction
Virtual reproduction of optical material properties is an important
task for many computer graphics applications. Recently, bidirectional
texture functions (BTFs) [Dana et al. 1999] have become
quite popular for photo-realistic rendering of surfaces. BTFs can
represent a huge variety of different materials. They can be easily
integrated into any modern rendering system which offers programmable
surface shaders. BTFs of real materials can be optically
measured, they are known to be efficiently compressible and can be
used for real-time graphics rendering applications even on the web
using WebGL.
Alternatively, BTFs can be synthesized based on known microstructure.
This approach is especially interesting for computer
aided design of complex materials that cannot be represented by
simple BRDF or texture models. One challenging example is cloth
which exhibits complex single and multiple scattering of light between
millions of fibers. Cloth designers might want to edit the
optical properties of individual fibers, the geometric properties of
spun yarns and their overall composition using weave patterns or
knitting techniques and perform predictive rendering.
To this end, virtual gonio-reflectometer setups can be build which
compute the angular reflectance data for a virtual material sample.
Essentially, this means that light transport has to be simulated for
thousands of view and light directions. A naive solution would be
to build a virtual half-dome multi-view multi-light measurement
device and render e.g. 70 70 images (”BTF slices”) of a flat
material sample for 70 viewing and 70 lighting directions. Unfor-
tunately, rendering thousands of images, commonly done using a
path tracing approach, is extremely costly. To accelerate this process,
we take advantage of the fact that BTFs tend to contain many
very similar apparent bidirectional reflectance distribution functions
(ABRDFs). Exploiting this property, we reduce variance by
sharing radiance samples across different BTF texels.
In the context of image denoising, non-local means filtering techniques
[Buades et al. 2005] have become popular. Here, the original
value of a pixel is replaced by a weighted average of all pixels
in the image showing a similar distribution of surrounding pixels.
However, the technique breaks down for renderings with a very low
signal to noise ratio.
作者:
C.R.CAN
时间:
2012-2-8 23:32
精典,学习了!
作者:
tc
时间:
2012-3-4 23:24
很经典,很实用,学习了!
作者:
C.R.CAN
时间:
2012-4-5 23:30
有意思!学习了!
作者:
奇
时间:
2012-5-14 23:21
不错哦,顶一下......
作者:
晃晃
时间:
2012-7-23 23:25
你们都躲开,我来顶
作者:
菜刀吻电线
时间:
2012-8-22 00:20
读铁系缘分,顶铁系友情
作者:
晃晃
时间:
2012-9-21 23:24
很经典,很实用,学习了!
作者:
菜刀吻电线
时间:
2012-9-25 23:26
不错哦,谢谢楼主
作者:
C.R.CAN
时间:
2012-9-26 23:26
不错 非常经典 实用
作者:
奇
时间:
2012-11-30 23:20
我就看看,我不说话
作者:
晃晃
时间:
2013-2-25 23:28
发了那么多,我都不知道该用哪个给你回帖了,呵呵
作者:
tc
时间:
2013-3-12 23:29
有意思!学习了!
欢迎光临 纳金网 (http://go.narkii.com/club/)
Powered by Discuz! X2.5