Siamese Networks based Deep Fusion Framework for Multi-source Satellite Imagery

Hannan Adeel, Javaria Tahir, M Mohsin Riaz, Syed Sohaib Ali
2022 IEEE Access  
A critical aim of pansharpening is to fuse coherent spatial and spectral features from panchromatic and multispectral images respectively. This study proposes deep siamese network based pansharpening model as a two-stage framework in a multiscale setting. In the first stage, a siamese network learns a common feature space between panchromatic and multispectral bands. The second stage follows by fusing the output feature maps of the siamese network. The parameters of these two stages are shared
more » ... cross scales in order to add spatial information consistently (across scales). The spectral information is preserved by adding appropriate skip connections from input multispectral image. Multi-level network parameters sharing mechanism in pyramidal reconstruction of pansharpened image, better preserves spatial and spectral details simultaneously. Experimental work carried out using deep siamese network in multi-scale setting (to obtain inter-band similarity among different sensor data) outperforms several latest pansharpening methods. INDEX TERMS Pansharpening, image fusion, deep-learning, siamese networks, remote sensing, depth-of-field.
doi:10.1109/access.2022.3143847 fatcat:24uapkabuzapvhsa6oiapsln6a