<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Image fusion is a method of combining the Multispectral (MS) and Panchromatic (PAN) images into one image contains more information than any of the input. Image fusion aim is to decrease unknown and weaken common data in the fused output image at the same time improving necessary information. Fused images are helpful in various applications like, remote sensing, computer vision, biometrics, change detection, image analysis and image classification. Conventional fusion methods are having some side effects like assertive spatial information and uncertain color information is an usually the problem in PCA and wavelet transform based fusion is a computationally in depth process. In order to overcome these side effects and to propose alternative soft computing fusion approach for conventional fusion methods we exploit image fusion using fuzzy logic technique to fuse two source images obtained from different sensors to enhance both spectral and spatial information. The proposed work here further compared with two common fusion methods like, principal component analysis (PCA) and wavelet transform along with quality assessment metrics. Exploratory outputs demonstrated in order that fuzzy based image fusion technique can actively retains more information compared to PCA and wavelet transform approaches while enhancing the spatial and spectral resolution of the satellite images. </p></abstract>

Image fusion is a method of combining the Multispectral (MS) and Panchromatic (PAN) images into one image contains more information than any of the input. Image fusion aim is to decrease unknown and weaken common data in the fused output image at the same time improving necessary information. Fused images are helpful in various applications like, remote sensing, computer vision, biometrics, change detection, image analysis and image classification. Conventional fusion methods are having some side effects like assertive spatial information and uncertain color information is an usually the problem in PCA and wavelet transform based fusion is a computationally in depth process. In order to overcome these side effects and to propose alternative soft computing fusion approach for conventional fusion methods we exploit image fusion using fuzzy logic technique to fuse two source images obtained from different sensors to enhance both spectral and spatial information. The proposed work here further compared with two common fusion methods like, principal component analysis (PCA) and wavelet transform along with quality assessment metrics. Exploratory outputs demonstrated in order that fuzzy based image fusion technique can actively retains more information compared to PCA and wavelet transform approaches while enhancing the spatial and spectral resolution of the satellite images.

Satellite image fusion using fuzzy logic

Acta Universitatis Sapientiae, Informatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Satellite image fusion using fuzzy logic"}

Image fusion is a method of combining the Multispectral (MS) and Panchromatic (PAN) images into one image contains more information than any of the input....

Satellite image fusion using fuzzy logic

Pubblicato online: 30 dic 2016

Pagine: 241 - 253

Ricevuto: 08 lug 2016

DOI: https://doi.org/10.1515/ausi-2016-0011

Parole chiave
Fusion, MS, PAN, Fuzzy Logic, PCA, Wavelet Transform

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Satellite image fusion using fuzzy logic

Pubblicato online: 30 dic 2016

Pagine: 241 - 253

Ricevuto: 08 lug 2016

DOI: https://doi.org/10.1515/ausi-2016-0011

Parole chiaveFusion, MS, PAN, Fuzzy Logic, PCA, Wavelet Transform

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Parole chiave
Fusion, MS, PAN, Fuzzy Logic, PCA, Wavelet Transform