Introduction to Digital Image Processing

This is an introductory course in processing grey-scale and color images — taught at the graduate level. This course will cover both mathematical fundamentals and implementation. It will introduce students to the basic principles of processing digital signals and how those principles apply to images. These fundamentals will include sampling theory, transforms in appearance and geometry, filtering and object segmentation. The course will also cover a series of basic imageprocessing problems including enhancement, reconstruction, segmentation, feature detection, and compression. Assignments will include several projects with software implementations and analysis of real data, and with emphasis on a project report with summary of the approach and critical assessment of results and experiments.