5 papers
AeroLLE: Constrained Pseudo-Supervision for Nighttime Aerial Image Enhancement with the AeroNight-1.5K Benchmark
Wei Lu, Hongyuan Liu, Si-Bao Chen
Nighttime aerial image enhancement is challenged by spatially nonuniform exposure, mixed illumination, and weak structural evidence, while registered normal-light targets are diffi…
LWGANet: Addressing Spatial and Channel Redundancy in Remote Sensing Visual Tasks with Light-Weight Grouped Attention
Wei Lu, Xue Yang, Si-Bao Chen
Light-weight neural networks for remote sensing (RS) visual analysis must overcome two inherent redundancies: spatial redundancy from vast, homogeneous backgrounds, and channel red…
LEGNet: A Lightweight Edge-Gaussian Network for Low-Quality Remote Sensing Image Object Detection
Wei Lu, Si-Bao Chen, Hui-Dong Li +4
Remote sensing object detection (RSOD) often suffers from degradations such as low spatial resolution, sensor noise, motion blur, and adverse illumination. These factors diminish f…
Unsupervised Ultra-High-Resolution UAV Low-Light Image Enhancement: A Benchmark, Metric and Framework
Wei Lu, Lingyu Zhu, Si-Bao Chen
Low light conditions significantly degrade Unmanned Aerial Vehicles (UAVs) performance in critical applications. Existing Low-light Image Enhancement (LIE) methods struggle with th…
Real-World Remote Sensing Image Dehazing: Benchmark and Baseline
Zeng-Hui Zhu, Wei Lu, Si-Bao Chen +3
Remote Sensing Image Dehazing (RSID) poses significant challenges in real-world scenarios due to the complex atmospheric conditions and severe color distortions that degrade image…