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Fast Domain Decomposition for Global Image Smoothing

Title
Fast Domain Decomposition for Global Image Smoothing
Authors
Kim, YoungjungMin, DongboHam, BumsubSohn, Kwanghoon
Ewha Authors
민동보
Issue Date
2017
Journal Title
IEEE TRANSACTIONS ON IMAGE PROCESSING
ISSN
1057-7149JCR Link

1941-0042JCR Link
Citation
IEEE TRANSACTIONS ON IMAGE PROCESSING vol. 26, no. 8, pp. 4079 - 4091
Keywords
Edge-preserving image smoothingjoint image filteringweighted-least squaresalternating minimizationmajorization-minimization algorithm
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Indexed
SCI; SCIE; SCOPUS WOS
Document Type
Article
Abstract
Edge-preserving smoothing (EPS) can be formulated as minimizing an objective function that consists of data and regularization terms. At the price of high-computational cost, this global EPS approach is more robust and versatile than a local one that typically has a form of weighted averaging. In this paper, we introduce an efficient decomposition-based method for global EPS that minimizes the objective function of L-2 data and (possibly non-smooth and non-convex) regularization terms in linear time. Different from previous decomposition-based methods, which require solving a large linear system, our approach solves an equivalent constrained optimization problem, resulting in a sequence of 1-D sub-problems. This enables applying fast linear time solver for weighted-least squares and -L-1 smoothing problems. An alternating direction method of multipliers algorithm is adopted to guarantee fast convergence. Our method is fully parallelizable, and its runtime is even comparable to the state-of-the-art local EPS approaches. We also propose a family of fast majorization-minimization algorithms that minimize an objective with non-convex regularization terms. Experimental results demonstrate the effectiveness and flexibility of our approach in a range of image processing and computational photography applications.
DOI
10.1109/TIP.2017.2710621
Appears in Collections:
엘텍공과대학 > 컴퓨터공학과 > Journal papers
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