Advanced Digital Imaging Laboratory Using MATLAB(R) [Hardcover]

In this book, Prof. Yaroslavsky delivers a complete applied course in digital imaging aimed at advanced students and practitioners. Covering all areas of digital imaging, the text provides an outline of underlying principles of each topic before offering more than 80 MATLAB(R) based exercises. Subjects addressed embrace image digitization (discretization, quantization, compression), digital image formation and computational imaging, image resampling and building continuous image models, image and noise statistical characterization and diagnostics, statistical image models and pattern formation, image correlators for localization of objects, methods of image perfecting (denoising, deblurring), and methods of image enhancement.

1 Introduction
2 Image digitization
3 Digital image formation and computational imaging
4 Image resampling and building continuous image models
5 Image and noise statistical characterization and diagnostics
6 Statistical image models and pattern formation
7 Image correlators for detection and localization of objects
8 Methods of image perfecting
9 Methods of image enhancement

Leonid P Yaroslavsky is a professor emeritus at Tel Aviv University. A fellow of the Optical Society of America, Prof. Yaroslavsky has authored more than 100 papers on digital image processing and digital holography.Whether you are studying or already using digital imaging techniques, developing proficiency in the subject is not possible without mastering practical skills. In this book, Prof. Yaroslavsky delivers a complete applied course in digital imaging aimed at advanced students and practitioners. Covering all areas of digital imaging, the text provides an outline of outlying principles of each topic while offering more than 80 MATLAB(R) based exercises. Subjects addressed embrace image digitization (discretization, quantization, compression), digital image formation and clƒf