Fr. 76.00

Subpixel Mapping for Remote Sensing Images

English · Paperback / Softback

Shipping usually within 3 to 5 weeks

Description

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This book provides a complete overview of subpixel image processing methods, basic principles, and different subpixel mapping techniques based on single or multi-shift remote sensing images. Real-life applications are a great resource for understanding how and where to use subpixel mapping with different remote sensing imaging data.


List of contents

Introduction. Basic Principle of Sub-pixel Mapping. Sub-pixel Mapping Based on Single Remote Sensing Image. Subpixel Mapping Based on Multi-Shift Remote Sensing Images. Subpixel Mapping of Remote Sensing Imaging Based on Pansharpening Technology. Subpixel Mapping of Remote Sensing Image Based on Reconstruction then Classification. Application of Subpixel Mapping Technology in Remote Sensing Imaging.

About the author

Peng Wang earned his Ph.D. from the College of Information and Communications Engineering, Harbin Engineering University, Harbin, China, in 2018. He is currently an associate professor at the College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Jiangsu, China. His research interests include remote sensing imagery processing and machine learning. He has authored one book and more than 50 papers.
Lei Zhang earned his Ph.D. from the Graduate School of Chinese Academy of Sciences in 2008 and finished the postdoctoral program at Tsinghua University in 2010. From 2011 to 2012 he was an associate professor at the Chinese University of Hong Kong, and from 2012 to 2015 at the Shanghai Institute of Technical Physics of Chinese Academy of Sciences. Now he is a professor in Tongji University. His research interests include intelligent information processing and spatio-temporal applications.

Summary

This book provides a complete overview of subpixel image processing methods, basic principles, and different subpixel mapping techniques based on single or multi-shift remote sensing images. Real-life applications are a great resource for understanding how and where to use subpixel mapping with different remote sensing imaging data.

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