Wavelet-based signal processing and applications

Title: Wavelet Based Signal Processing and Applications

Semester: Seventh Semester for B Tech ECE (similar to S3 Mtech VLSI)

3-0-0, 3 Credits

Prerequisites: Linear Algebra, Digital Signal Processing, Signals and Systems

Review of Fourier Theory – Heisenberg’s Uncertainty Principle – Short Time Fourier Transform – Wavelet and MRA – Recap of Vector Spaces – Continuous Wavelet Transforms – Discrete Wavelet Transform – Scaling and Wavelet Functions – Filter Banks – Design of Orthogonal Wavelet Systems – Bi-Orthogonal Wavelet – Introduction to Lifting Scheme – Dealing with Signal Boundaries – Multi Wavelet – Frequency Domain Approach – Design of Wavelet – Wavelet in Image Processing – Bio Medical Applications – Data Compression – EZW Algorithm – De Noising – Edge Detection – Object Isolation – Audio Coding – Communication Application – Channel Coding – Speckle Removal – Image Fusion.

Text Books/References:

1. Stéphane Mallat, “A Wavelet Tour of Signal Processing”, 3rd ed. Academic Press, 2008.

2. G. Strang and T. Q. Nguyen, “Wavelets and Filter Banks,” Wellesley-Cambridge Press, 1996.

3. K. P. Soman and K. I. Ramachandran, “Insight into Wavelets From Theory to Practice,” Prentice Hall, 2004.

4. R. M. Rao and Ajith S. Bopardikar, “Wavelet Transforms-Introduction to Theory and Applications,” Pearson Education, 1998.

5. Ingrid Daubechies, “Ten Lectures on Wavelets”, SIAM: Society for Industrial and Applied Mathematics; 1^st edition, 1992.