Paper Info
Title
Edge-preserving decompositions for multi-scale tone and detail manipulation
Abstract
Many recent computational photography techniques decompose an image into a piecewise smooth base layer, containing large scale variations in intensity, and a residual detail layer capturing the smaller scale details in the image. In many of these applications, it is important to control the spatial scale of the extracted details, and it is often desirable to manipulate details at multiple scales, while avoiding visual artifacts. In this paper we introduce a new way to construct edge-preserving multi-scale image decompositions. We show that current base- detail decomposition techniques, based on the bilateral filter, are limited in their ability to extract detail at arbitrary scales. Instead, we advocate the use of an alternative edge-preserving smoothing operator, based on the weighted least squares optimization frame- work, which is particularly well suited for progressive coarsening of images and for multi-scale detail extraction. After describing this operator, we show how to use it to construct edge-preserving multi-scale decompositions, and compare it to the bilateral filter, as well as to other schemes. Finally, we demonstrate the effectiveness of our edge-preserving decompositions in the context of LDR and HDR tone mapping, detail enhancement, and other applications. CR Categories: I.3.3 (Computer Graphics): Picture/Image Generation—Display algorithms; I.4.3 (Image Processing and Computer Vision): Enhancement—Grayscale Manipulation; I.4.9 (Image Processing and Computer Vision): Applications;
Year
DOI
Venue
2008
10.1145/1360612.1360666
ACM Trans. Graph.
Keywords
Field
DocType
spatial scale,tone mapping,bilateral filtering
Computer vision,Visual artifact,Computer graphics (images),Computer science,Computational photography,Smoothing,Tone mapping,Artificial intelligence,Operator (computer programming),Bilateral filter,Piecewise,Edge-preserving smoothing
Journal
Volume
Issue
ISSN
27
3
0730-0301
Citations 
PageRank 
References 
422
12.08
35
Authors
4
Search Limit
100422
Name
Order
Citations
PageRank
Zeev Farbman178927.40
Raanan Fattal22440119.13
Dani Lischinski35465340.85
Richard Szeliski4213002104.74