Signal and Image Processing for Remote Sensing, 2/e (Hardcover)

Continuing in the footsteps of the pioneering first edition, Signal and Image Processing for Remote Sensing, Second Edition 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 form, signal processing can contribute significantly in extracting information from remotely sensed waveforms or time series data. This book combines both, providing a unique balance between the role of signal processing and image processing.

Featuring contributions from worldwide experts, this book continues to emphasize mathematical approaches. Not limited to satellite data, it also considers signals and images from hydroacoustic, seismic, microwave, and other sensors. Chapters cover important topics in signal and image processing and discuss techniques for dealing with remote sensing problems. Each chapter offers an introduction to the topic before delving into research results, making the book accessible to a broad audience.

This second edition reflects the considerable advances that have occurred in the field, with 23 of 27 chapters being new or entirely rewritten. Coverage includes new mathematical developments such as compressive sensing, empirical mode decomposition, and sparse representation, as well as new component analysis methods such as non-negative matrix and tensor factorization. The book also presents new experimental results on SAR and hyperspectral image processing.

The emphasis is on mathematical techniques that will far outlast the rapidly changing sensor, software, and hardware technologies. Written for industrial and academic researchers and graduate students alike, this book helps readers connect the "dots" in image and signal processing.

New in This Edition

The second edition includes four chapters from the first edition, plus 23 new or entirely rewritten chapters, and 190 new figures. New topics covered include:

• Compressive sensing
• The mixed pixel problem with hyperspectral images
• Hyperspectral image (HSI) target detection and classification based on sparse representation
• An ISAR technique for refocusing moving targets in SAR images
• Empirical mode decomposition for signal processing
• Feature extraction for classification of remote sensing signals and images
• Active learning methods in classification of remote sensing images
• Signal subspace identification of hyperspectral data
• Wavelet-based multi/hyperspectral image restoration and fusion

The second edition is not intended to replace the first edition entirely and readers are encouraged to read both editions of the book for a more complete picture of signal and image processing in remote sensing. See Signal and Image Processing for Remote Sensing (CRC Press 2006).

《遙感信號與影像處理第二版》延續了開創性的第一版，探索了最新的遙感問題信號和影像處理方法。儘管大多數衛星數據以影像形式存在，但信號處理在從遙感波形或時間序列數據中提取信息方面也能做出重要貢獻。本書結合了兩者，提供了信號處理和影像處理之間獨特的平衡。

本書由全球專家貢獻，繼續強調數學方法。它不僅限於衛星數據，還考慮了水聲學、地震、微波和其他傳感器的信號和影像。各章節涵蓋了信號和影像處理的重要主題，並討論了處理遙感問題的技術。每個章節在深入研究結果之前都提供了該主題的介紹，使本書適合廣大讀者。

第二版反映了該領域取得的重大進展，其中27章中有23章是全新的或完全重寫的。內容包括壓縮感知、經驗模態分解和稀疏表示等新的數學發展，以及非負矩陣和張量分解等新的成分分析方法。本書還介紹了關於合成孔徑雷達（SAR）和高光譜影像處理的新實驗結果。

本書強調的是數學技術，這些技術將遠遠超越快速變化的傳感器、軟件和硬件技術。本書針對工業和學術研究人員以及研究生，幫助讀者在影像和信號處理中建立關聯。

第二版包括第一版的四章，以及23章全新的或完全重寫的章節，還有190個新圖。新增的主題包括：

- 壓縮感知
- 高光譜影像中的混合像素問題
- 基於稀疏表示的高光譜影像（HSI）目標檢測和分類
- 合成孔徑雷達（SAR）影像中移動目標的ISAR技術重新聚焦
- 信號處理的經驗模態分解
- 遙感信號和影像的特徵提取
- 遙感影像分類中的主動學習方法
- 高光譜數據的信號子空間識別
- 基於小波的多/高光譜影像恢復和融合

第二版並不完全取代第一版，建議讀者閱讀兩版以獲得更完整的遙感信號和影像處理知識。另外，第一版的書名為《遙感信號與影像處理》（CRC Press 2006）。