𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Signal and image processing for remote sensing

✍ Scribed by Chen, Chi-hau


Publisher
CRC/Taylor & Francis
Year
2007
Tongue
English
Leaves
687
Edition
0
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


Most data from satellites are in image form, thus most books in the remote sensing field deal exclusively with image processing. However, signal processing can contribute significantly in extracting information from the remotely sensed waveforms or time series data. Pioneering the combination of the two processes, Signal and Image Processing for Remote Sensing provides a balance between the role of signal processing and image processing in remote sensing.

Featuring contributions from worldwide experts, this book emphasizes mathematical approaches. Divided into two parts, Part I examines signal processing for remote sensing and Part II explores image processing. Not limited to the problems with data from satellite sensors, the book considers other sensors which acquire data remotely, including signals and images from infrasound, seismic, microwave, and satellite sensors. It covers a broader scope of issues in remote sensing information processing than other books in this area.

With rapid technological advances, the mathematical techniques provided will far outlast the sensor, software and hardware technologies. Focusing on methodologies of signal processing and image processing in remote sensing, this book discusses unique techniques for dealing with remote sensing problems

✦ Table of Contents


Content: 1. On the normalized Hilbert transform and its applications in remote sensing / Steven R. Long and Norden E. Huang --
2. Statistical pattern recognition and signal processing in remote sensing / Chi Hau Chen --
3. A universal neural network-based infrasound event classifier / Fredric M. Ham and Ranjan Acharyya --
4. Construction of seismic images by ray tracing / Enders A. Robinson --
5. Multi-dimensional seismic data decomposition by higher order SVD and unimodal ICA / Nicolas Le Bihan, Valeriu Vrabie and Jerome I. Mars --
6. Application of factor analysis in seismic profiling / Zhenhai Wang and Chi Hau Chen --
7. Kalman filtering for weak signal detection in remote sensing / Stacy L. Tantum, Yingyi Tan and Leslie M. Collins.

✦ Subjects


Remote sensing -- Data processing. Image processing. Signal processing. Télédétection -- Informatique. Traitement d'images. Traitement du signal. Bildverarbeitung. Fernerkundung. Signalverarbeitung.


πŸ“œ SIMILAR VOLUMES


Signal and Image Processing for Remote S
✍ C.H. Chen πŸ“‚ Library πŸ“… 2006 πŸ› CRC Press 🌐 English

Most data from satellites are in image form, thus most books in the remote sensing field deal exclusively with image processing. However, signal processing can contribute significantly in extracting information from the remotely sensed waveforms or time series data. Pioneering the combination of th

Signal and Image Processing for Remote S
✍ C.H. Chen πŸ“‚ Library πŸ“… 2012 πŸ› CRC Press 🌐 English

<P>Continuing in the footsteps of the pioneering first edition, <STRONG>Signal and Image Processing for Remote Sensing, Second Edition</STRONG> explores the most up-to-date signal and image processing methods for dealing with remote sensing problems. Although most data from satellites are in image f

Signal and Image Processing for Remote S
✍ C.H. Chen (editor) πŸ“‚ Library πŸ“… 2024 πŸ› CRC Press 🌐 English

<p><span>Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of </span><

Signal and Image Processing for Remote S
✍ C.H. Chen (editor) πŸ“‚ Library πŸ“… 2024 πŸ› CRC Press 🌐 English

<p><span>Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of </span><