Remote Sensing Image Processing

Recent developments in Earth observation technology have significantly diversified remote sensing images. Large-scale remote sensing images, characterized by their extensive volume and coverage of geographic areas, are increasingly accessible. Therefore, how to automatically, accurately, and efficiently process remote sensing images has been a primary research focus in the remote sensing community.

For decades, this field has attracted considerable attention and witnessed remarkable advancements. However, various challenges still remain, spurring continuous efforts and contributions to enhance, analyze, and understand remote sensing images via advanced image processing techniques.

Submissions addressing theories and applications of remote sensing image processing are welcome in this section. Manuscripts not focused on remote sensing imagery will not be accepted for review. Potential topics include but are not limited to:

• Image enhancement and restoration;
• Remote sensing image classification and segmentation;
• Optical/Hyperspectral/Multispectral/Infrared/Radar/Sonar image analysis;
• Remote sensing object-based image understanding;
• Object/change/anomaly detection;
• Geospatial image fusion;
• Multi-modal/multi-sensor/multi-temporal data fusion;
• Machine learning for remote sensing image processing;
• Image augmentation techniques;
• Image registration, stitching and georeferencing;
• Remote sensing image compression.