Change detection is an essential and widely utilized task in remote sensing that aims to
detect and analyze changes occurring in the same geographical area over time, which has …

As a fundamental task in remote sensing (RS) observation of the earth, change detection
(CD) using hyperspectral images (HSI) features high accuracy due to the combination of the …

Hyperspectral image change detection (HSI-CD) is a challenging task that focuses on
identifying the differences between multitemporal HSIs. The recent advancement of …

Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting
changes in the Earth's surface, finding wide applications in urban planning, disaster …

Hyperspectral image (HSI) has rich spatial–spectral information, high spectral correlation,
and large redundancy between information. Due to the sparse background distribution of …

Deep learning (DL) approaches have been extensively applied to change detection in
hyperspectral images (HSIs). However, the majority of them encounter scarcity of training …

Deep learning (DL)-based methods have recently shown great promise in bitemporal
change detection (CD). Existing discriminative methods based on convolutional neural …

Deep learning-based hyperspectral image (HSI) change detection (CD) approaches have a
strong ability to leverage spectral-spatial-temporal information through automatic feature …

Hyperspectral images (HSIs) are generally distorted by various types of damage and
degradation due to limited imaging conditions. Hence, noise reduction is an essential …

With the aid of transformers, significant progress has been achieved in hyperspectral image
change detection (HSI-CD) in recent times. Nonetheless, most contemporary detection …