TY - JOUR
T1 - Edge-preserving decompositions for multi-scale tone and detail manipulation
AU - Farbman, Zeev
AU - Fattal, Raanan
AU - Lischinski, Dani
AU - Szeliski, Richard
PY - 2008/8/1
Y1 - 2008/8/1
N2 - 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 basedetail 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 framework, 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.
AB - 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 basedetail 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 framework, 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.
KW - Bilateral filter
KW - Detail enhancement
KW - Digital darkroom
KW - Edge-preserving smoothing
KW - High dynamic range
KW - Image abstraction
KW - Multi-scale image decomposition
KW - Tone mapping
UR - http://www.scopus.com/inward/record.url?scp=49249119306&partnerID=8YFLogxK
U2 - 10.1145/1360612.1360666
DO - 10.1145/1360612.1360666
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AN - SCOPUS:49249119306
SN - 0730-0301
VL - 27
JO - ACM Transactions on Graphics
JF - ACM Transactions on Graphics
IS - 3
M1 - 67
ER -