Last updated: January 7, 2013UTSADepartment of ELECTRICAL ENGINEERINGEE-4623/5263Digital FilteringSyllabus-AppendixInstructor:Sos Agaian, Ph.D., Peter Flawn ProfessorOffice:EB 1.540Office Hours: Mondays, Wednesdays 4:30PM -6:30PM or by appointment. If you do need to reach me, the best way is to come to my office hours. The next best way is by e-mail. However, please be aware that I receive a large volume of student e-mails, so I will not be able to respond right away)Lecture Mondays, Wednesdays 7:00 PM 8:15PM, Phone: XXXXXXXXXX; E-mail: XXXXXXXXXX:http://engineering.utsa.edu/~sagaian/Appendix: ABET” Folder and Projects “ABET” Folder: Each students is required to submit a notebook or folder containing all graded materials for the course (projects, etc.) at the end of semester."Please bring a notebook (file) organized in the following format to the final exam:1. Course syllabus and the list of Projects2. Graded ProjectsItems 1-3 are required. Other materials such as your class notes could be added at the end (optional). If you don't submita notebook containing all the required items, you will receive a grade of "IN"(incomplete) for the course which will be removed only when a completed notebook is turned in. Your actual grade will be based only for the work completed during semester. Lateassignmentsthat are submitted within one week of the due date will receive a 10% point penalty.Assignment submitted after the 1 week deadline will receive a 25% point penalty.An important element of this course is the project where the students, working individually or as part of a team, will work on a problem in digital filteringThere are three major steps in the project:?Design and implement your filtering routine in MATLAB (or C) based on the provided special signals and imagesand ground truth data.?Test your routine with the training images by the evaluation program.?Performance of your routine will be tested in the class presentation with a test image by the same evaluation program.The course project will consist of either a theoretical analysis of a digital filter or the design, programming, and simulation of a filtering algorithm for a particular application (or some combination of the two). Project Team:Students are encouraged to work in-group, but working alone is fine as well. Note, the project partners may share “Boiler plate” common material, but should emphasize the individual contributions in the report. The proposed work for each individual should be identified. For example, if a two-person team is working on lowpass filtering then each student can develop separate lowpass filtering algorithms and they can compare the performance.
2The project shouldbe described in readable English in a report. There will also be a 15 minute oral presentation. The report should provide appropriate references to the literature and a comparative discussion with existing methods. Suggestions for projects will be handed out in class, but creativity in developing a topic will be considered in the grade. The projects can be developed for any available platform. The project grade will be based on the creativity and technical content of the project and on the quality of the presentation and participation in the discussion of the other project presentations. Example of the projectAssignments: The following is a list of suggested topics. You may come up with your topics. Please contact the instructor about other project proposals.PotentialProjects Project-1 (Computer or hardware implementation, samples)?Develop the programs that implement several noise models(Gaussian, White, Thermal , Impulse (salt-and-pepper) ,Generalized Gamma dist, uniform, Rayleigh, Exponentialand. Periodic). Display the results. ?Develop a program that implements the nonlinear filters (for example,develop the programs that implement the Positive and Negative Weighted Median Filters, Mean square error (MSE) measurement is used to evaluate the filter performance.Display the results.?Develop a program that implements simple linearand nonlinearfilters (for example, Develop the programs that implement the Positive and Negative Weighted Median FiltersSpatial Domain Filterssuch as Arithmetic mean,geometric mean, Harmonic mean filter, Max and min filters, median filter, Contra-harmonic mean filter, Midpoint filter, order statistics filters, Adaptive Filters)Mean square error (MSE) measurement is used to evaluate the filter performance.Display the results.?Develop the programs that implement the Morphological filters. Mean square error (MSE) measurement is used to evaluate the filter performance.Display the results.?Develop a program that implements an adaptive filter.Mean square error (MSE) measurement is used to evaluate the filter performance.Display the results.?Develop a program that implements the Alpha-trimmedand Homomorphic filters.Mean square error (MSE) measurement is used to evaluate the filter performance.Display the results.Project-2 (Computer or hardwareimplementation,samples)?Develop a program that implements Boolean function based filters?Develop a program that implements simple linear/nonlinear filter banksand de-noising procedures.?Develop a program for computing the discrete Fourier and windowing Fourier transformof a signal. Display the results.?Develop a program that implements the DFbased image enhancement algorithms. Display the results.?Develop a program that implements the DFbased edge detectionalgorithms. Display the results.?Develop a program that implements the DFbased signal prediction/ extrapolation algorithms. Display the results.?Develop a program that implements the Fourier transform based FIR filters, (including Cesaro, and Vallee Poussinfilters), and use the program for signal filtering. Display the results.?Develop a program that implements the cosine transform based filters, (including Cesaro, and Vallee Poussinfilters), and use the program for signal filtering. Display the results. Project-3 (Computer or hardwareimplementation, sample)?Develop a program that implements the second-order Peaking and Notching filters. Display the results?Verify (experimentally) the basic properties of the Chebyshev system. Develop a program that implements the Chebyshev filters. Display the results?Verify (experimentally) the basic properties of the Butterworth system. Develop a program that implements the classical Butterworth filter. Display the results?Analysis of Gaussian and Butterworth Band-reject and Notch filters on Enhancing and Cleaning Noisy Images?The primary goal of this project is to introduce the concept of the Coordinate Logic Filter and provide examples of two applications of the filter in the area of image processing. The first application,the majority coordinate logic filter, is described and the results of applying the filter to an image with varying paper (impulse) noise are compared. In the last section we will see how a coordinate logic filter can be used to quickly implement an edge detection function. Matlab will be used to execute all examples shown in this project. Specifically it can be used to generate the noise, add the noise to the image, create the filter, apply the filter to the image, measure the filter results, and execute the edge detection algorithm.