Detail publikačního výsledku

Wavelet Transform for Image Analysis. In the Proceedings of

ŠKORPIL, V.; ŠŤASTNÝ, J.

Originální název

Wavelet Transform for Image Analysis. In the Proceedings of

Anglický název

Wavelet Transform for Image Analysis. In the Proceedings of

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The wavelet transform is a comparatively new and fast developing method for analysing signals. The main advantage of applying the wavelet transform to the detection of edges in an image is the possibility of choosing the size of the details that will be detected. The size of detected edges is set by the wavelet scale. In the case of the discrete wavelet transform the choice of the scale is performed by multiple signal passage through the wavelet filter. When processing a 2-D image, the wavelet analysis is performed separately for the horizontal and the vertical function. The vertical and the horizontal edges are thus detected separately. The wavelet transform will split the input signal into two components. One contains the low-frequency (LP) part of input signal, which corresponds to major changes in the function (individual objects in the image, etc.). The other part contains the high-frequency (HP) part of input signal, which corresponds to details in the function (noise, edges, etc.). This signal component is not processed on the next level of transformation.

Anglický abstrakt

The wavelet transform is a comparatively new and fast developing method for analysing signals. The main advantage of applying the wavelet transform to the detection of edges in an image is the possibility of choosing the size of the details that will be detected. The size of detected edges is set by the wavelet scale. In the case of the discrete wavelet transform the choice of the scale is performed by multiple signal passage through the wavelet filter. When processing a 2-D image, the wavelet analysis is performed separately for the horizontal and the vertical function. The vertical and the horizontal edges are thus detected separately. The wavelet transform will split the input signal into two components. One contains the low-frequency (LP) part of input signal, which corresponds to major changes in the function (individual objects in the image, etc.). The other part contains the high-frequency (HP) part of input signal, which corresponds to details in the function (noise, edges, etc.). This signal component is not processed on the next level of transformation.

Klíčová slova

wavelet transform, edge detection, image

Klíčová slova v angličtině

wavelet transform, edge detection, image

Autoři

ŠKORPIL, V.; ŠŤASTNÝ, J.

Rok RIV

2011

Vydáno

29.09.2003

Nakladatel

IEEE

Místo

Tomsk, Ruska

ISBN

0-7803-7854-7

Kniha

In Proceedings of the IEEE-Siberian Conference on Control and Communications. SIBCON-2003

Strany od

50

Strany počet

5

URL

knihovnaUTKO

BibTex

@inproceedings{BUT32453,
  author="Vladislav {Škorpil} and Jiří {Šťastný}",
  title="Wavelet Transform for Image Analysis. In the Proceedings of",
  booktitle="In Proceedings of the IEEE-Siberian Conference on Control and Communications. SIBCON-2003",
  year="2003",
  pages="5",
  publisher="IEEE",
  address="Tomsk, Ruska",
  isbn="0-7803-7854-7",
  url="knihovnaUTKO"
}