Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …

Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …

Multisource image registration is challenging due to intensity, rotation, and scale differences
among the images. Considering the characteristics and differences in multisource remote …

Semantic segmentation is a fundamental but challenging problem of pixel-level remote
sensing (RS) data analysis. Semantic segmentation tasks based on aerial and satellite …

Real-time scene comprehension is the basis for automatic electric power inspection.
However, existing RGB-based scene comprehension methods may achieve unsatisfied …

Due to the complementary nature of optical and synthetic aperture radar (SAR) images, their
alignment is of increasing interest. However, due to the significant radiometric differences …

The characteristics of very high-resolution (VHR) remote sensing images (RSIs) have higher
spatial resolution inherently and are easier to obtain globally compared with hyperspectral …

Remote sensing image matching is the basis upon which to obtain integrated observations
and complementary information representation of the same scene from multiple source …

The necessary prerequisite for effective data fusion is the strict registration of low-resolution
hyperspectral images (LR-HSIs) and high-resolution multispectral images (HR-MSIs) …

High-resolution thermal infrared (TIR) remote sensing images can more accurately retrieve
land surface temperature and describe the spatial pattern of urban thermal environment. The …