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Mathematical Principles of Remote Sensing: Making Inferences from Noisy Data

Mathematical Principles of Remote Sensing: Making Inferences from Noisy Data

List Price: $89.95
Your Price: $89.95
Product Info Reviews

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Rating: 4 stars
Summary: Remote Sensing or Image Reconstruction
Review: If you are looking for a book on transforming satellite data into pretty pictures or land-use plots there are much better texts. Try those by Lillesand and Kieffer or Schowengerdt. However, if you are interested in the general area of inverse problems, especially unfolding the complex physical processes that produced the satellite imagery to extract information then this is a great book for you. The early chapters deal in general terms with the image formation process and sources of noise. These chapters are unsatisfying. The real gem of this book is Chapter 7 in which the author derives a robust, direct solution for linear matrix problems. Chapter 10 Integral Equations, Chapter 11 Iteration, and Chapter 12 Resolution and Noise are also very enlightening. The solutions and techniques covered in this text are equally applicable to other inverse problems such as image restoration or computerized tomography (CT).

The downside to this book is that it has quite a few errors.

Rating: 4 stars
Summary: Remote Sensing or Image Reconstruction
Review: If you are looking for a book on transforming satellite data into pretty pictures or land-use plots there are much better texts. Try those by Lillesand and Kieffer or Schowengerdt. However, if you are interested in the general area of inverse problems, especially unfolding the complex physical processes that produced the satellite imagery to extract information then this is a great book for you. The early chapters deal in general terms with the image formation process and sources of noise. These chapters are unsatisfying. The real gem of this book is Chapter 7 in which the author derives a robust, direct solution for linear matrix problems. Chapter 10 Integral Equations, Chapter 11 Iteration, and Chapter 12 Resolution and Noise are also very enlightening. The solutions and techniques covered in this text are equally applicable to other inverse problems such as image restoration or computerized tomography (CT).

The downside to this book is that it has quite a few errors.


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