Image Fusion in Remote Sensing

Conventional and Deep Learning Approaches
Erscheinungsjahr 2021
ISBN: 978-1-63639-076-5
Verlag: Morgan & Claypool Publishers

Buch, Englisch, 93 Seiten, Hardback, Format (B × H): 191 mm x 235 mm

Reihe: Synthesis Lectures on Image, Video, and Multimedia Processing

Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites. This book addresses image fusion approaches for remote sensing applications. Both conventional and deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches include component substitution, multi-resolution, and model-based algorithms. Then, the recently developed deep learning approaches involving single-objective and multi-objective loss functions are discussed. Experimental results are provided comparing conventional and deep learning approaches in terms of both low-resolution and full-resolution objective metrics that are commonly used in remote sensing. The book is concluded by stating anticipated future trends in pansharpening or image fusion in remote sensing.

Autoren/Hrsg.

Fachgebiete

• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Technische Wissenschaften Technik Allgemein Technische Instrumentierung
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik

Inhaltsverzeichnis

- Preface
- Introduction
- Introduction to Remote Sensing
- Conventional Image Fusion Approaches in Remote Sensing
- Deep Learning-Based Image Fusion Approaches in Remote Sensing
- Unsupervised Generative Model for Pansharpening
- Experimental Studies
- Anticipated Future Trend
- Authors' Biographies
- Index