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Department of Electrical Engineering
EE 5263.002 Wavelets with Multimedia Applications (Credit 3)
Syllabus, Spring 2006
Catalog description: This course will provide an introduction to the wavelet transform theory and some associated applications. The wavelet transform has been perhaps the most exciting development in the last decade to bring together researchers in several different fields such as signal and image processing, communications, computer science, and mathematics. The wavelet transform expresses a given signal, image in terms of simpler signals built from a mother wavelet. The combination of exceptional theory, efficient algorithms, and successful applications makes the field of wavelets quite exciting.
Convergence originates with classical orthogonal representations and proceeds through wavelet decomposition. The topics include wavelet applications to
- multimedia signal processing (multimedia signal enhancement, de-noising, compression)
- multimedia security (watermarking, and steganography)
Steganography (literally "covered writing" in Greek) is the ancient art of hiding messages (mostly inside the physical object) so that they are not detectable. Throughout the centruies, many steganographic techniques have been developed. Modern steganography is a secure communication of information by embedding a secret-message within a "cover" digital multimedia without any perceptual distortion of the cover media, so the presence of the hidden message is indiscernible.
Textbooks: Chun-Shien Lu, Multimedia Security: Steganography and Digital Watermarking Techniques for Protection of Intellectual Property, Idea Group Publishing, ISBN: 1591401925 Metin Akay, Time Frequency and Wavelets in Biomedical Signal Processing, Wiley-IEEE Press, ISBN: 0780311477
References: Jianhong Shen, Image Processing and Analysis: Variational, Pde, Wavelet, and Stochastic Methods Society for Industrial and Applied Mathematics Agaian's Lecture Notes
Prerequisite: EE 5143 Linear Systems and Control
Intended Audience: The course should be of interest to student working in all areas of signal and image processing, speech analysis, astronomy, biology, computer graphics, acoustics, medicine, information, security, and seismology.
Coordinator: Sos S. Agaian, PhD., Professor of Electrical Engineering
Class: 7:00pm-8:15pm, EB 2.04.06
Office Hours: M-W 5:00-7:00pm, after class, or by appointment
Email: sagaian@utsa.edu
Course Objectives: This course will help the students to:
- understand the following fast orthogonal transforms: Fourier, Cosine, Haar, Slant, and Walsh
- understand the basic principles of one and two dimensional wavelets and subband decomposition
- understand the international compression standards, JPEG, JPEG2000, and H.261
- learn a basic watermarking, steganography, and steganalysis, and multimedia signal enhancement and de-noising techniques.
Topics:
- Signal Representation: Fourier, Cosine, Sine, Hartley, Haar, Slant, Walsh and Short-time orthogonal transforms
- Image and video international compression standards: JPEG, H.261
PROJECT 1: Presentation and Report
- Subband decompositions
- 1-D and 2-D Wavelets: construction, properties, decomposition, and reconstruction, multiresolution and analysis
- Wavelet Packets
PROJECT 2: Presentation and Report
- Multimedia Signal Processing (multimedia signal enhancement, de-noising, compression)
- Multimedia Security (Watermarking and Steganography)
PROJECT 3: Presentation and Report
Performance Criteria:
- Objective 1: The students will demonstrate knowledge of the basic principles of Orthogonal transforms, wavelets, and fractals
- Objective 2: The students will have a practical understanding of the basic principles of signal and image de-noising, compression, watermarking, and steganalysis
- Objective 3: The students will have an ability to work effectively in multi-disciplinary teams.
- Objective 4: The students will have ability to present technical information clearly in both oral and written formats.
- Grading: The project will be graded upon based on the level of involvement of these methods, the complexity of the project, the level of success in the projects.
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