arXiv Open Access 2021

A Generative Model Method for Unsupervised Multispectral Image Fusion in Remote Sensing

Arian Azarang Nasser Kehtarnavaz
Lihat Sumber

Abstrak

This paper presents a generative model method for multispectral image fusion in remote sensing which is trained without supervision. This method eases the supervision of learning and it also considers a multi-objective loss function to achieve image fusion. The loss function incorporates both spectral and spatial distortions. Two discriminators are designed to minimize the spectral and spatial distortions of the generative output. Extensive experimentations are conducted using three public domain datasets. The comparison results across four reduced-resolution and three full-resolution objective metrics show the superiority of the developed method over several recently developed methods.

Topik & Kata Kunci

Penulis (2)

A

Arian Azarang

N

Nasser Kehtarnavaz

Format Sitasi

Azarang, A., Kehtarnavaz, N. (2021). A Generative Model Method for Unsupervised Multispectral Image Fusion in Remote Sensing. https://arxiv.org/abs/2102.03908

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓