Format:
1 Online-Ressource(XI, 81 p.)
Edition:
1st ed. 2021.
ISBN:
9783031022562
Series Statement:
Synthesis Lectures on Image, Video, and Multimedia Processing
Content:
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.
Content:
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.
Additional Edition:
ISBN 9783031002175
Additional Edition:
ISBN 9783031011283
Additional Edition:
ISBN 9783031033841
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031002175
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031011283
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031033841
Language:
English
DOI:
10.1007/978-3-031-02256-2
