Announcements:
July 20: Usebackpack.com will be used to share resources such lecture slides and demos, and collected project reports and codes. So it is important that you register yourself at the course page available in usebackpack.com with the alphanumeric code given in today's lecture (first lecture).
Course Objective:
The course will cover advanced digital signal processing topics mainly targeted at applications such as image and video signal processing. Some basic signal processing concepts will be touched upon as well. An important component of the course will be a project in an application domain.
Reference Books & Resources:
- Digital Signal Processing: Principles, Algorithms and Applications by John G. Proakis, Dimitris G. Manolakis
- Signals and Systems by Alan V. Oppenheim and Alan S. Willsky
- Discrete-Time Signal Processing by Alan V. Oppenheim and Ronald W. Schafer
- Wavelet Transforms: Introduction to Theory and Applications by Raghuveer M. Rao and Ajit S. Bopardikar
- Probability, Random Variables and Stochastic Processes by Athanasios Papoulis and S. Unnikrishna Pillai
- Fundamentals of Nonlinear Digital Filtering by Jaakko Astola and Pauli Kuosmanen
- Nonlinear Digital Filters by Ioannis Pitas and Anastasios N. Venetsanopoulos
- Fundamentals of Digital Image Processing by Anil K. Jain
- Digital Image Processing by William K. Pratt
- Digital Image Processing by R. Gonzalez and R. Woods
- Color Image Processing and Applications by Konstantinos N. Plataniotis and Anastasios N. Venetsanopoulos
& Research Papers
Specific references for the demos will be provided during the demos.
Class Information:
Class Timings - Wednesday 12.00 - 12.55 HRS, Thursday 11.00 - 11.55 HRS and Friday 9.00 to 10.55 HRS
Venue - F-300, Electronics & Electrical Communication Engineering Building.
Office hours - Friday – 11.30pm to 1.30pm.
Course Syllabus:
Discrete Signals
Discrete Systems
Z-transform
Frequency Analysis of Discrete Signals and Systems
Discrete Fourier Transform and Applications
Signal Transforms and Applications
Sampling and Reconstruction
Multirate DSP and Applications
Gaussian & Gabor Filters and Pyramids, and Applications
Wavelet Decomposition and Applications
Random Signal Processing and Applications
Nonlinear Signal Processing and Applications
Advanced Digital Filtering Applications
Application Domains: Audio, Image and Video Processing
Evaluation:
A term project, 4 monthly tests, and mid-sem and end-sem exams will be used to evaluate performance in this course:
Monthly tests x class attendance – 6%
Project – 14% (4% for innovation)
Mid-sem – 30% (fixed by institute)
End-sem – 50% (fixed by institute)
Lecture Resources: (will be posted in usebackpack.com after the lecture is done)
Usebackpack Link: https://www.usebackpack.com/iitkgp/courses/e51de4