Asee peer logo

Teaching Signals And Systems Through Visualization With Image Processing

Download Paper |


1997 Annual Conference


Milwaukee, Wisconsin

Publication Date

June 15, 1997

Start Date

June 15, 1997

End Date

June 18, 1997



Page Count


Page Numbers

2.392.1 - 2.392.14

Permanent URL

Download Count


Request a correction

Paper Authors

author page

Richard R. Schultz

Download Paper |

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

1 Session 3532

Teaching Signals and Systems through Visualization with Image Processing Richard R. Schultz University of North Dakota

Abstract: Most signals and systems courses teach abstract concepts such as convolution and Fourier transform theory using only one-dimensional (1-D) signals. However, real-life 1-D signals such as speech and music do not possess easily recognizable visual forms, and thus the effect of applying a particular signal processing technique to the data is difficult to visualize. Applying various algorithms to 2-D image data, on the other hand, results in obvious visual changes when the input and output images are compared side-by-side. This paper describes a set of image processing experiments which can help students comprehend many important systems-related concepts, including spatial convolution, space-frequency duality, image compression, spatial and contrast enhancement, degradation due to noise, and image restoration. By viewing the results of a particular image processing algorithm, an intuitive understanding of the corresponding 1-D signal processing concept is acquired.

1. Introduction It has been said that a single picture is worth a thousand words. Digital image processing is becoming an integral part of science and engineering for this very reason: visualization aids immensely in the understanding of large data sets. Furthermore, an intuitive understanding of abstract systems-related topics such as convolution and Fourier transform theory can be acquired when these algorithms are applied to images. Often, these concepts are taught to electrical engineering students in a signals and systems course which deals exclusively with 1-D signals. However, the data smoothing effect of a lowpass filter can be better visualized by comparing an input image to the corresponding blurry filtered image. Similarly, seeing the edges detected by a 2-D highpass filter applied to an image is a far more dramatic visual effect than that provided by the corresponding 1-D filter applied to a speech signal. Once a systems concept has been made intuitively clear, understanding the mathematical definitions and explanations should become easier for the students. A set of laboratory exercises have been developed for a course in digital image processing which will aid in teaching systems-related concepts such as spatial convolution, space-frequency duality, image compression, spatial and contrast enhancement, signal degradation due to noise, and image restoration. All laboratory exercises were originally implemented using the C programming language on a UNIX computer system. Students in a digital image processing course taught by the author during the fall semester of 1996 were provided with source code templates of a number of useful image processing algorithms. These C source code templates were deliberately missing critical components

This work was supported in part by the National Science Foundation Faculty Early Career Development (CAREER) Program, grant number MIP-9624849. In addition, this material is based upon work supported in part by the U.S. Army Research Office under contract number DAAH04-96-1-0449.

Schultz, R. R. (1997, June), Teaching Signals And Systems Through Visualization With Image Processing Paper presented at 1997 Annual Conference, Milwaukee, Wisconsin.

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 1997 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015