NOC:Foundations of Wavelets and Multirate Digital Signal Processing

Lecture 1 - Introduction

Lecture 2 - Origin of wavelets

Lecture 3 - Haar wavelet

Lecture 4 - Dyadic wavelet

Lecture 5 - Dilates and translates of Haar wavelet

Lecture 6 - L2 norm of a function

Lecture 7 - Piecewise constant representation of a function

Lecture 8 - Ladder of subspaces

Lecture 9 - Scaling function of Haar wavelet

Lecture 10 - Demonstration: Piecewise constant approximation of functions

Lecture 11 - Vector representation of sequences

Lecture 12 - Properties of norm

Lecture 13 - Parsevals theorem

Lecture 14 - Equivalence of functions and sequences

Lecture 15 - Angle between Functions and their Decomposition

Lecture 16 - Additional Information on Direct-Sum

Lecture 17 - Introduction to filter banks

Lecture 18 - Haar Analysis filter bank in Z-domain

Lecture 19 - Haar Synthesis filter bank in Z-domain

Lecture 20 - Moving from Z-domain to frequency domain

Lecture 21 - Frequency Response of Haar Analysis Low pass Filter bank

Lecture 22 - Frequency Response of Haar Analysis High pass Filter bank

Lecture 23 - Ideal Two-band Filter bank

Lecture 24 - Disqualification of Ideal Filter bank

Lecture 25 - Realizable Two-band Filter bank

Lecture 26 - Demonstration: DWT of images

Lecture 27 - Relating Fourier transform of scaling function to filter bank

Lecture 28 - Fourier transform of scaling function

Lecture 29 - Construction of scaling and wavelet functions from filter bank

Lecture 30 - Demonstration: Constructing scaling and wavelet functions.

Lecture 31 - Conclusive Remarks and Future Prospects