Deep learning has achieved great success in learning features from massive remote
sensing images (RSIs). To better understand the connection between three feature learning …

Building footprint is a primary dataset of an urban geographic information system (GIS)
database. Therefore, it is essential to establish a robust and automated framework for large …

Optimizing color consistency across multiple images is a crucial step in creating accurate
digital orthophoto maps (DOMs). However, current color balance methods that rely on a …

The relative radiometric correction for Level-0 images captured by spaceborne push-broom
imaging system faces the problems of vignetting, chromatic aberration, brightness saturation …

Multispectral fluorescence imaging is an effective tool for studying plant stress responses
and diagnosing nutrient deficiencies. To address the influence of fluorescence shadow error …

The self-supervised learning (SSL) technique, driven by massive unlabeled data, is
expected to be a promising solution for semantic segmentation of remote sensing images …

Earth observation satellites can capture optical images under different temporal, climatic
conditions, and platforms exhibit substantial differences in color and brightness, leading to …

Color correction for multiview images is a fundamental yet challenging task to generate a
color-consistent composite image and has important applications in remote sensing and 3-D …

Given a source UAV (unmanned aerial vehicle) image I s and a target UAV image I t, it is a
challenging problem to correct the color of all target pixels so that the subjective and …

This study proposes an improved color correction algorithm based on Fuzzy c-means (FCM)
clustering algorithm and Wallis filtering to address the problem of spectral drift in image …