Image Fusion in Remote Sensing : Conventional and Deep Learning Approaches / by Arian Azarang, Nasser Kehtarnavaz.

Format:

Book

Author/Creator:

Azarang, Arian., Author.

Kehtarnavaz, Nasser., Author.

Series:

Synthesis Lectures on Image, Video, and Multimedia Processing, 1559-8144

Language:

English

Subjects (All):

Engineering.

Electrical engineering.

Signal processing.

Technology and Engineering.

Electrical and Electronic Engineering.

Signal, Speech and Image Processing .

Local Subjects:

Technology and Engineering.

Electrical and Electronic Engineering.

Signal, Speech and Image Processing .

Physical Description:

1 online resource (XI, 81 p.)

Edition:

1st ed. 2021.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

Summary:

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.

Contents:

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.

ISBN:

9783031022562

3031022564