Digital Image Processing

Intended as a practical guide, the book takes the reader from basic concepts to up-to-date research topics in digital image processing. Only little special knowledge in computer sciences is required since many principles and mathematical tools widely used in natural sciences are also applied in digital image processing thus the reader with a general background in natural science gets an easy access to the material presented. The book discusses the following topics: image acquisition and digitization; linear and nonlinear filter operations; edge detection; local orientation and texture; fast algorithms on pyramidal and multigrid data structures; morphological operations to detect the shape of objects; segmentation and classification. Further chapters deal with the reconstruction of three-dimensional objects from projections and the analysis of stereo images and image sequences with differential, correlation, and filter algorithms. Many examples from different areas show how the reader can use digital image processing as an experimental tool for image data acquisition and evaluation in his or her research area.

Intended as a practical guide, the book takes the reader from basic concepts to up-to-date research topics in digital image processing. Only little special knowledge in computer sciences is required since many principles and mathematical tools widely used in natural sciences are also applied in digital image processing thus the reader with a general background in natural science gets an easy access to the material presented. The book discusses the following topics: image acquisition and digitization; linear and nonlinear filter operations; edge detection; local orientation and texture; fast algorithms on pyramidal and multigrid data structures; morphological operations to detect the shape of objects; segmentation and classification. Further chapters deal with the reconstruction of three-dimensional objects from projections and the analysis of stereo images and image sequences with differential, correlation, and filter algorithms. Many examples from different areas show how the reader can use digital image processing as an experimental tool for image data acquisition and evaluation in his or her research area.