Beschreibung:
Omer Demirkaya, Musa H. Asyali, Prasanna K. Sahoo
This text explains complex, theory-laden topics in image processing through examples and MATLAB® algorithms. It provides these algorithms to help scientists and researchers quickly identify the most effective solution method for a particular problem at hand. The authors emphasize three-dimensional processing and analysis as well as statistical and stochastic modeling. They cover the new areas of nonlinear diffusion filtering and PDE-based image filtering, address relatively advanced topics, such as Markov random field-based image segmentation, and highlight applications with images from medicine and biology. They also include real-world examples and exercises in every chapter.
Medical Imaging Systems. Fundamental Tools for Image Processing and Analysis. Probability Theory for Stochastic Modeling of Images. Two-Dimensional Fourier Transform. Nonlinear Diffusion Filtering. Intensity-Based Image Segmentation. Image Segmentation by Markov Random Field Modeling. Deformable Models. Image Analysis. Applications. Appendices.