Geometric Description of Images as Topographic Maps.

Caselles, Vicent; Pascal Monasse

ISBN 10: 364204610X / ISBN 13: 9783642046100

Verlag: Berlin, Springer., 2010

Beschreibung

XVII, 186 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped/gestempelt. Lecture Notes in Mathematics, Vol.1984 Sprache: Englisch.

Bestandsnummer des Verkäufers 5319DB

Bibliografische Details

• Titel: Geometric Description of Images as Topographic Maps.
• Verlag: Berlin, Springer.
• Erscheinungsjahr: 2010
• Sprache: Englisch
• ISBN-10: 364204610X
• ISBN-13: 9783642046100
• Einband: Softcover
• Gewicht: 408 Gramm
• Verkäuferkataloge:
  • Mathematik

Über diesen Titel

Inhaltsangabe

This book discusses the basic geometric contents of an image and presents a treedatastructuretohandleite?ciently.Itanalyzesalsosomemorphological operators that simplify this geometric contents and their implementation in termsofthe datastructuresintroduced.It?nallyreviewsseveralapplications to image comparison and registration, to edge and corner computation, and the selection of features associated to a given scale in images. Let us ?rst say that, to avoid a long list, we shall not give references in this summary; they are obviously contained in this monograph. A gray level image is usually modeled as a function de?ned in a bounded N domain D? R (typically N = 2 for usual snapshots, N=3formedical images or movies) with values in R. The sensors of a camera or a CCD array transform the continuum of light energies to a ?nite interval of values by means of a nonlinear function g. The contrast change g depends on the pr- ertiesofthesensors,butalsoontheilluminationconditionsandthere?ection propertiesofthe objects,andthoseconditionsaregenerallyunknown.Images are thus observed modulo an arbitrary and unknown contrast change.

Von der hinteren Coverseite

This volume discusses the basic geometric contents of an image and presents a tree data structure to handle those contents efficiently. The nodes of the tree are derived from connected components of level sets of the intensity, while the edges represent inclusion information. Grain filters, morphological operators simplifying these geometric contents, are analyzed and several applications to image comparison and registration, and to edge and corner detection, are presented.
The mathematically inclined reader may be most interested in Chapters 2 to 6, which generalize the topological Morse description to continuous or semicontinuous functions, while mathematical morphologists may more closely consider grain filters in Chapter 3. Computer scientists will find algorithmic considerations in Chapters 6 and 7, the full justification of which may be found in Chapters 2 and 4 respectively. Lastly, all readers can learn more about the motivation for this work in the image processing applications presented in Chapter 8.