M310: Digital Image Processing

Course Objective This two-day course enables attendees to develop their own imaging solutions using Mathematica and the Digital Image Processing application package and gives the attendees a detailed, comprehensive demonstration of Mathematica's relevant features and capabilities.

Course Summary This course presents the theory and practice of digital image processing with Mathematica and focuses on the Digital Image Processing package. The features and capabilities of the package are demonstrated, and numerous examples and practical hands-on exercises are included. The material is presented as a sequence of eight one-hour lectures. Each lecture covers a major image processing topic, typically consisting of a discussion of the basic theoretical concepts and including examples that illustrate relevant, practical imaging problems. The lectures are followed by exercise sessions to help attendees understand the material and to provide a focused and practical learning experience.

Presenter The course is presented by Mariusz Jankowski, the developer of the Digital Image Processing package. Professor Jankowski has over six years of teaching experience with Mathematica and over 12 years of image processing research experience.

Target Audience The course is designed primarily for people who want and need to analyze and process imaging data with Mathematica. Attendees typically have wide-ranging backgrounds and include engineers and professionals in the physical, life, and medical sciences.

Delivery Type Courses are delivered as instructor-led classes in computer classroom facilities or as online classes delivered over the web. Course topics are presented with alternating sessions of lectures and exercises.

Syllabus This basic course is organized into eight segments.

Introduction
Lists, matrices, and images; basics of programming with Mathematica; image representation and display
Image Histogram and Point Operations
Image resizing, interpolation and decimation, affine spatial transformations (rotation), and higher-order spatial transformations (warp)
Linear Processing
Convolution and correlation, linear filtering, FIR filters, blurring, sharpening, and edge detection
Selective Processing
Block processing, region-of-interest processing, and line profiles
Nonlinear Processing
Nonlinear noise reducing filters (e.g., median, outlier, and adaptive) and image morphology
Frequency-Domain Processing
Fourier analysis and unitary image transforms: DFT, DCT, DHT, and DWT
Performance and Extensions
Packed arrays, Compile, J/Link, and Java Advanced Programming (JAI)

Course Materials Each attendee will be provided with Mathematica course notebooks and access to the current version of Mathematica. The course notebooks require Mathematica or Mathematica Player. For attendees participating in classroom-based sessions, course materials are distributed in print and on CD-ROM, and are yours to keep; a computer running Mathematica is available for your use during class. For attendees participating in online classes, a download of the course materials is provided; a temporary Mathematica training license is provided upon request.

Prerequisites Course attendees are expected to have basic familiarity with Mathematica approximately equivalent to that provided by "M101: A First Course in Mathematica." A basic-level knowledge of signal/image processing concepts and experience with introductory computer programming are also helpful.