Satellite image processing

Daniel Capella Zanotta , Matheus Pinheiro Ferreira , Maciel Zortea

The book introduces beginners to satellite image processing, but doesn’t limit itself to them, advancing and deepening in mathematical details on techniques and algorithms for more experienced users. A result of years of the authors’ experience in the areas of teaching and research, Satellite image processing addresses in a wide-encompassing and didactic way the main techniques and challenges faced in the digital treatment and classification of images acquired by sensors, illustrating them step-by-step. It’s an increasingly indispensable knowledge for weather prediction and agriculture, environmental monitoring, territorial and urban planning, management and support of catastrophes and many other fields of knowledge.

In its first six chapters, the book covers from basic concepts of remote sensing, image calibration and correction and histogram to orthogonal transformations, models of spectral mixture, calculation of physical indexes, arithmetic operations and passing filters in the space and frequency domains. It includes another three chapters dealing with the probabilistic classification of data: among other classifiers, it discusses calibration validation sampling, tests and segmentation and classification by objects, through different methodologies.

Richly illustrated, with practical examples and proposed exercises, it constitutes an important reference for students, researchers and professionals working in the multiple areas of remote sensing application.

Original title
Processamento de imagens de satélite
Year of publication

About the authors

Daniel Capella Zanotta

Daniel Capella Zanotta has a bachelor’s degree in Physics by the Federal University of Rio Grande Foundation (Furg, 2007), a Master’s degree in Remote Sensing by the Federal University of Rio Grande do Sul (UFRGS, 2010), and a PhD in Remote Sensing by the National Institute of Space Researches (Inpe, 2014). He wcts as a professor in the Geoprocessing course of the Federal Institute of Education, Science and Technology of Rio Grande do Sul (IFRS), Rio Grande campus, and as a collaborator in the post-graduation program in Remote Sensing of the Federal University of Rio Grande do Sul (UFRGS), where he is responsible for the Digital Image Processing discipline.

Matheus Pinheiro Ferreira

Matheus Pinheiro Ferreirais a graduate in Forest Engineering by the Federal University of Paraná (UFPR, 2010), with complimentary studies in the University of Freiburg (Germany), and Master (2012) and Doctor (2017) in Remote Sensing by the National Institute of Space Researches (Inpe). His doctorate thesis was awarded Honorable Mention by the 2018 Capes Thesis Awards. Currently he’s associate professor in the Cartography Engineering session of the Military Institute of Engineering (IME), where he teaches disciplines related to Remote Sensing and Digital Image Processing in a graduate and post graduate level.

Maciel Zortea

Maciel Zortea graduated in Civil Engineering (2001) and achieved a Master’s in Remote Sensing (2004) by the Federal University of Rio Grande do Sul (UFRGS) and a PhD in Space Science and Engineering by Genoa University (Italy) (2007). He works as a researcher in the Research Laboratory of IBM Brazil (IBM Research), where he develops methodologies for image analyses and patter recognition, with applications in Remote Sensing. His experience in research projects and development includes post-doctorates in Hyperspectral Computing in the University of Extramadura (Spain) and Dermoscopic Imaging Analysis in the University of Tromsø (Norway).