Detail publikačního výsledku

Image Extrapolation using sparse methods

ŠPIŘÍK, J.; ZÁTYIK, J.

Originální název

Image Extrapolation using sparse methods

Anglický název

Image Extrapolation using sparse methods

Druh

Článek recenzovaný mimo WoS a Scopus

Originální abstrakt

Image extrapolation is the specific application in image processing. You have to extrapolate the image for example when you want to process the given image piecewise. When the border patches are incompleted you must extrapolate them to the given size. Nowadays,some basic extrapolations, e.g. linear, polynomial etc. are used. The advanced methods are presented in this paper. We are using the algorithms that are based on finding the sparse solutions in underdetermined systems of linear equations. Three algorithms are presented for image extrapolation. First one is the K-SVD algorithm. K-SVD is the algorithm that trains a dictionary which allows the optimal sparse representation. Second one is Morphological Component Analysis (MCA) which is based on Independent Component Analysis (ICA). The last is the Expectation Maximization (EM) algorithm. This algorithm is statistics-based. These three algorithms for image extrapolation are compared on the real images.

Anglický abstrakt

Image extrapolation is the specific application in image processing. You have to extrapolate the image for example when you want to process the given image piecewise. When the border patches are incompleted you must extrapolate them to the given size. Nowadays,some basic extrapolations, e.g. linear, polynomial etc. are used. The advanced methods are presented in this paper. We are using the algorithms that are based on finding the sparse solutions in underdetermined systems of linear equations. Three algorithms are presented for image extrapolation. First one is the K-SVD algorithm. K-SVD is the algorithm that trains a dictionary which allows the optimal sparse representation. Second one is Morphological Component Analysis (MCA) which is based on Independent Component Analysis (ICA). The last is the Expectation Maximization (EM) algorithm. This algorithm is statistics-based. These three algorithms for image extrapolation are compared on the real images.

Klíčová slova

image extrapolation, sparse, K-SVD, MCA, EM

Klíčová slova v angličtině

image extrapolation, sparse, K-SVD, MCA, EM

Autoři

ŠPIŘÍK, J.; ZÁTYIK, J.

Rok RIV

2014

Vydáno

03.06.2013

Nakladatel

EDIS - Publishing Institution of Zilina University

Místo

Zilina

ISSN

1335-4205

Periodikum

Communications

Svazek

2013

Číslo

2a

Stát

Slovenská republika

Strany od

174

Strany do

179

Strany počet

6

BibTex

@article{BUT100541,
  author="Jan {Špiřík} and Ján {Zátyik}",
  title="Image Extrapolation using sparse methods",
  journal="Communications",
  year="2013",
  volume="2013",
  number="2a",
  pages="174--179",
  issn="1335-4205"
}