This book is a quick introduction, at a graduate level, to the field of computational complexity. It aims at presenting a collection of classical results in the field, rather than a comprehensive overview of complexity. It includes chapters on circuit complexity, proof complexity (a subfield of complexity that is rarely presented in similar textbooks) and randomized algorithms.
The material from which the book arises has been used as a graduate special topics course at McMaster University in Canada, the Jagiellonian University in Poland and the University of Colorado at Boulder in the U.S.A. The book provides a peek into powerful methods that have been used in attacks against the fundamental question of theoretical computer science, namely the famous P=NP question. It is the techniques themselves that have been emphasized by the Author, rather than the results obtainable by employing them. Thus, an important feature of the book is precisely that it affords a quick introduction to these techniques. For this reason the book might be of interest to anyone starting to work on problems in the fascinating field of computational complexity.

Whenever images taken at different times, from different viewpoints, and/or by different sensors need to be compared, merged, or integrated, image registration is required.
Registration, also known as alignment, fusion, or warping, is the process of transforming data into a common reference frame.
This book provides an overview of state-of-the-art registration techniques from theory to practice, plus numerous exercises designed to enhance reader's understanding of the principles and mechanisms of the described techniques. It also provides, via a supplementary Web page, free access to FAIR.m, a package that is based on the MATLAB® software environment, which enables readers to experiment with the proposed algorithms and explore the presented examples in more depth.