Wavelet Transform for Image Analysis. In the Proceedings of

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F03%3APU40199" target="_blank" >RIV/00216305:26220/03:PU40199 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Wavelet Transform for Image Analysis. In the Proceedings of

Original language description

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 bedetected. 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 analysisis 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

Czech name

Wavelet Transform for Image Analysis. In the Proceedings of

Czech description

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 bedetected. 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 analysisis 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

Type

D - Article in proceedings

CEP classification

JA - Electronics and optoelectronics

OECD FORD branch

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Project

<a href="/en/project/GA102%2F03%2F0560" target="_blank" >GA102/03/0560: New methods of providing and monitoring auality of services in next generation networks</a><br>

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2003

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

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

ISBN

0-7803-7854-7

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

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Publisher name

IEEE

Place of publication

Tomsk, Ruska

Event location

Tomsk

Event date

Oct 1, 2003

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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