[IPOL discuss] [IPOL announce] new article: Cartoon + Texture Image Decomposition by the TV-L1 Model

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2014/103/

Vincent Le Guen,
Cartoon + Texture Image Decomposition by the TV-L1 Model,
Image Processing On Line, 4 (2014), pp. 204–219.
http://dx.doi.org/10.5201/ipol.2014.103

Abstract
We consider the problem of decomposing an image into a cartoon part and 
a textural part. The geometric and smoothly-varying component, referred 
to as cartoon, is composed of object hues and boundaries. The texture is 
an oscillatory component capturing details and noise. Variational models 
form a general framework to obtain u + v image decompositions, where 
cartoon and texture are forced into different functional spaces. The 
TV-L1 model consists in a L1 data fidelity term and a Total Variation 
(TV) regularization term. The L1 norm is particularly well suited for 
the cartoon+texture decomposition since it better preserves geometric 
features than the L2 norm. The TV regularization has become famous in 
inverse problems because it enables to recover sharp variations. 
However, the nondifferentiability of TV makes the underlying problems 
challenging to solve. There exists a wide literature of variants and 
numerical attempts to solve these optimization problems. In this paper, 
we present an implementation of a primal dual algorithm proposed by 
Antonin Chambolle and Thomas Pock applied to this image decomposition 
problem with the TV-L1 model. A thorough experimental comparison is 
performed with a recent filter pair proposed in IPOL for the 
cartoon+texture decomposition.


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