Multivariate Image Processing (Hardcover)

Multivariate imagery is now a very common tool in numerous applications, ranging from satellite remote sensing and astrophysics to biomedical imagery, monitoring of the environment or industrial inspection. Multivariate must be understood in th emost general way: color and multispectral imaging, but also multimodal, multisource or multitemporal imagery. In all the cases, the multivariate image corresponds to a set of standard grey level images.

The availability of the additional diversity, be it spectral temporal and s.o., provides an invaluable source of information, enabling to consider a wide range of new applications. However, in order to address these applications, theoretical developments are required in terms of signal and image processing, or, more generally speaking, information processing. As a matter of fact, most of the standard algorithms designed for grey level images do not generalize easily to multidimensional spaces and some specific derivations are required.

This book aims at presenting the most recent advances in signal and image processing for the analysis of multivariate data. It should be helpful for electrical engineers, PhD students and researcher working in the field of signal processing, but also for any engineer dealing with some specific application where multidimensional data are processed.

多變量影像現在在許多應用中都是一個非常常見的工具，從衛星遙感和天體物理學到生物醫學影像、環境監測或工業檢測。多變量必須以最一般的方式來理解：包括彩色和多光譜成像，以及多模態、多來源或多時序影像。在所有情況下，多變量影像對應於一組標準灰度影像。

額外多樣性的可用性，無論是光譜、時間等，提供了寶貴的信息來源，使得可以考慮各種新的應用。然而，為了應對這些應用，需要在信號和影像處理方面進行理論發展，或者更一般地說，信息處理。事實上，大多數針對灰度影像設計的標準算法不容易推廣到多維空間，需要一些特定的推導。

本書旨在介紹多變量數據分析的信號和影像處理的最新進展。這對於電氣工程師、博士生和從事信號處理領域的研究人員非常有幫助，同時也適用於任何處理多維數據的特定應用的工程師。