Steven L Tanimoto
GEN ST 162
Small intensive seminar focusing on the natural world taught during Early Fall Start led by faculty representing a wide spectrum of academic disciplines and interests. Offered: A.
Basics of digital image representation; color systems; geometric transformations and distortions; symmetry; transformation groups; image effects; stereograms; anamorphosis; photomosaics; filtering; Fourier transform; basics of programming in Python, including control structures, loops, user-defined functions, recursion, and basic concepts of object-oriented programming; basic concepts of image analysis and computational photography; high-dynamic-range imaging.
Student learning goals
estimate memory requirements for images
perform enhancement of images using software tools and mathematical formulas
control color in an image by manipulating hue, saturation, and brightness
understand fundamental concepts in image processing including sampling, quantization, filtering, and using the Fourier transform
write simple programs in the Python programming language
relate image transformations and syntheses to the particular technical and mathematical techniques used to create them
General method of instruction
a combination of lectures, lab activities, homework problems, quizzes, portfolio production, and group project.
A little familiarity with digital cameras and computers. Normal high-school math.
Class assignments and grading
Exercises at the end of chapters of the reading. They may involve applying the ideas covered, or simple paper-and-pencil calculations, or in some cases, trying out something on a computer.
Grades will be based on total points earned during the course. Points can be earned in assignments, quizzes, worksheets, the portfolio, and the group project.