This course explores the role of mathematics in image processing and covers the major concepts and techniques, including sampling, transforms, enhancement, restoration, compression, and image analysis. Hands-on programming is a central feature. Poisson processes, Markov chains, with applications to the natural and social sciences. Also includes mathematical bases of common statistical tests with applications, sampling, hypothesis testing, and distributions commonly used in statistics. Includes a survey of current hardware, software, and standardization efforts.
Laboratories use elementary and advanced graphics terminals and microcomputers.
Includes applications and a research project. The course focuses on the relational model, with emphasis on information analysis, normalization, database design, and queries. Includes an overview of distributed and object-relational database systems. Applications examples are drawn from databases like Ms-SQL Server and Oracle, and programming environments like Delphi. Computer Science I, Introduction to C Programming I or equivalent programming experience.