Filipović, Marko; Kopriva, Ivica; Cichocki, Andrzej (2012) Inpainting color images in learned dictionary. In: 20th European Signal Processing Conference (EUSIPCO 2012) (27 August 2012 - 31 August 2012) Bukurešt, Rumunjska.
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Sparse representation of natural images over redundant dictionary enables solution of the inpainting problem. A major challenge, in this regard, is learning of a dictionary that is well adapted to the image. Efficient methods are developed for grayscale images represented in patch space by using, for example, K-SVD or independent component analysis algorithms. Here, we address the problem of patch space-based dictionary learning for color images. To this end, an image in RGB color space is represented as a collection of vectorized 3D patch tensors. This leads to the state-of-the-art results in inpainting random and structured patterns of missing values as it is demonstrated in the paper.
|Item Type:||Conference or workshop item published in conference proceedings (UNSPECIFIED)|
|Uncontrolled Keywords:||Learned Dictionary; Independent Component Analysis; Color Image; Inpainting|
|Subjects:||NATURAL SCIENCES > Mathematics > Applied Mathematics and Mathematical Modeling
TECHNICAL SCIENCES > Computing > Data Processing
|Divisions:||Division of Laser and Atomic Research and Development|
|Depositing User:||Marko Filipović|
|Date Deposited:||12 May 2015 14:14|
|Last Modified:||12 May 2015 14:14|
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