Remote sensing image fusion based on PCA and wavelets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F23%3A63570458" target="_blank" >RIV/70883521:28140/23:63570458 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-981-19-7524-0_3" target="_blank" >https://link.springer.com/chapter/10.1007/978-981-19-7524-0_3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-19-7524-0_3" target="_blank" >10.1007/978-981-19-7524-0_3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Remote sensing image fusion based on PCA and wavelets

Popis výsledku v původním jazyce

Remote sensing, in the recent past, has witnessed continuous developments in the field of environment, agriculture and security. The satellites obtain the information in two domains—spectral resolution and spatial resolution which are highlighted in the Low-Resolution Multi-Spectral (LRMS) and the Panchromatic (PAN) images, respectively. Remote sensing image fusion aims to integrate this complimentary information of the PAN and the LRMS images. In this paper, this has been achieved through Principal Component Analysis (PCA) and Discrete Wavelet Transformation (DWT). The proposed fusion approach involves extraction of the Ist Principal Component (PC) of the LRMS image while simultaneously performing Morphological Hat Transformation on PAN image. The resultant images undergo Discrete Wavelet Transformation to produce approximation (cA) and detail (cD) coefficients. These coefficients are fused using appropriate fusion rules, and the resultant images are synthesized using Inverse Discrete Wavelet Transformation (IDWT) to produce the final fused image. The results have been evaluated which are presented in the later sections. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Název v anglickém jazyce

Remote sensing image fusion based on PCA and wavelets

Popis výsledku anglicky

Remote sensing, in the recent past, has witnessed continuous developments in the field of environment, agriculture and security. The satellites obtain the information in two domains—spectral resolution and spatial resolution which are highlighted in the Low-Resolution Multi-Spectral (LRMS) and the Panchromatic (PAN) images, respectively. Remote sensing image fusion aims to integrate this complimentary information of the PAN and the LRMS images. In this paper, this has been achieved through Principal Component Analysis (PCA) and Discrete Wavelet Transformation (DWT). The proposed fusion approach involves extraction of the Ist Principal Component (PC) of the LRMS image while simultaneously performing Morphological Hat Transformation on PAN image. The resultant images undergo Discrete Wavelet Transformation to produce approximation (cA) and detail (cD) coefficients. These coefficients are fused using appropriate fusion rules, and the resultant images are synthesized using Inverse Discrete Wavelet Transformation (IDWT) to produce the final fused image. The results have been evaluated which are presented in the later sections. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

Smart Innovation, Systems and Technologies

ISBN

978-981-19752-3-3

ISSN

2190-3018

e-ISSN

2190-3026

Počet stran výsledku

9

Strana od-do

25-33

Název nakladatele

Springer Science and Business Media Deutschland GmbH

Místo vydání

Berlín

Místo konání akce

Aizawl

Datum konání akce

18. 6. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—