Abstract

Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-subsampled Contourlet Transform (NSCT) based multispectral image fusion model which integrates Principal Component Analysis (PCA), Phase congruency, directive contrast and entropy. The proposed methodology involves color transformation of input multispectral image. Two different fusion rules are then applied to the high-pass and low-pass subbands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

Autore Pugliese

• Lay Ekuakille Aime

Tutti gli autori

• Bhateja V. , Srivastava A. , Moin A. , Lay Ekuakille A.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2016

ISSN

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ISBN

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Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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