Image Fusion is a process of combining two or more images into a single image which is
more informative and hence more useful from an interpretation point of view. With the rapid …

Polarization can provide information largely uncorrelated with the spectrum and intensity.
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …

Synthetic aperture radar (SAR) and optical images often present different geometric
structures and texture features for the same ground object. Through the fusion of SAR and …

Background Tea is a valuable economic plant grown extensively in several Asian countries.
The accurate map** of tea plantations is critical for the growth and development of the tea …

With the development of remote sensing techniques, the fusion of multimodal data,
particularly hyperspectral-Light Detection And Ranging (HS-LiDAR) and hyperspectral-SAR …

Urban Scene classification using single source data is massively studied in remote sensing
field. However, single source only provides one certain perspective of the complicated urban …

Recently, remote sensing community has seen a surge in the use of multimodal data for
different tasks such as land cover classification, change detection and many more. However …

Using deep learning to improve the capabilities of high-resolution satellite images has
emerged recently as an important topic in automatic classification. Deep networks track …

In remote sensing, hyperspectral and polarimetric synthetic aperture radar (PolSAR) images
are the two most versatile data sources for a wide range of applications such as land use …

Hyperspectral imaging provides precise classification for land use and cover due to its
exceptional spectral resolution. However, the challenges of high dimensionality and limited …