Despite the fact that images constitute the main objects in computer
vision and image analysis, there is remarkably little concern about
their actual definition. In this book a complete account of image
structure is proposed in terms of rigorously defined machine concepts,
using basic tools from algebra, analysis, and differential geometry.
Machine technicalities such as discretisation and quantisation details
are de-emphasised, and robustness with respect to noise is manifest.
From the foreword by Jan Koenderink:
`It is my hope that the book will find a wide audience, including
physicists - who still are largely unaware of the general importance and
power of scale space theory, mathematicians - who will find in it a
principled and formally tight exposition of a topic awaiting further
development, and computer scientists - who will find here a unified and
conceptually well founded framework for many apparently unrelated and
largely historically motivated methods they already know and love. The
book is suited for self-study and graduate courses, the carefully
formulated exercises are designed to get to grips with the subject
matter and prepare the reader for original research.'