Image Signal Processing

By Prof. A.N. Rajagopalan   |   IIT Madras
Learners enrolled: 3670
This course spans both basics and advances in digital image processing. Starting from image formation in pin-hole and lens based cameras, it goes on to discuss geometric transformations and image homographies, a variety of unitary image transforms, several image enhancement methods, techniques for restoration of degraded images, and 3D shape recovery from images.

Any interested learners
PREREQUISITES Digital Signal Processing. Familiarity with linear algebra and probability theory is desirable.
INDUSTRIES  SUPPORT      : Google, Amazon, Facebook, Microsoft, KLA-Tencor, Qualcomm, Intel, Analog Devices, Philips, GE, Siemens and many more.
Course Status : Completed
Course Type : Elective
Duration : 12 weeks
Start Date : 14 Sep 2020
End Date : 04 Dec 2020
Exam Date : 20 Dec 2020
Enrollment Ends : 25 Sep 2020
Category :
  • Computer Science and Engineering
  • Biological Sciences & Bioengineering
  • Electrical, Electronics and Communications Engineering
  • Communication and Signal Processing
Level : Undergraduate/Postgraduate

Course layout

Week 1:  Introduction to Image Processing, Basics of Imaging, Geometric Transformations
Week 2:  Hierarchy of Transformations, Rotational Representation, Homography Computation
Week 3:  Research Challenges Involving Camera Motion, Basics of Real Aperture Camera, Lens as LSI System
Week 4:  Blur Kernels, Shape from X, Shape from Focus
Week 5:  Shape from Focus, Generalized Shape from Focus, Depth from Defocus (DFD) and Motion Blur
Week 6:  Unitary Image Transforms, From 1D to 2D Unitary Transforms, Higher Dimensional Unitary Transforms
Week 7:  2D Unitary Transforms, 2D Discrete Fourier Transform, 2D Discrete Cosine Transform
Week 8:  Karhunen-Loeve Transform (KLT), Applications of KLT, Singular Value Decomposition
Week 9:  Image Enhancement, Adaptive Thresholding, K-Means Clustering, ISODATA Clustering
Week 10: Contrast Stretching, Noise Filtering, Non-local Mean Filtering, Impulse Noise Filtering, Noise Filtering in Transform Domain, Illumination Compensation
Week 11: Image Restoration, Ill-posed Problems, Matrix Conditioning, Matrix Numerical Stability, Inverse filter for Image Deblurring, Regularization Theory
Week 12: Minimum Mean Square Error (MMSE) Estimator, Linear MMSE, Spatial Wiener Filter, Wiener filter in Fourier domain, Image Super-resolution, Super-resolution Examples

Books and references

Digital Image Processing by Rafael Gonzalez and Richard Woods.
The Essential Guide to Image Processing by Alan Bovik.

Instructor bio

Prof. A.N. Rajagopalan

IIT Madras
Dr. A.N. Rajagopalan is a Professor of Electrical Engineering at IIT Madras and specializes in the areas of Image Processing and Computer Vision. He is a Fellow of national and international academies, and Editorial Board member of flagship journals of IEEE in the above areas. He has co-authored two books.

Course certificate

•The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
•The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 20 December 2020, Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm. 
•Registration url: Announcements will be made when the registration form is open for registrations.
• The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
•Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.


This course will have an unproctored programming exam also apart from the Proctored exam, please check announcement section for date and time. The programming exam will have a weightage of 15% towards the Final score.

Final score = Assignment score + Unproctored programming exam score + Proctored Exam score

  •  Average assignment score =  The 25% weightage in the Final score from the assignments will be divided as follows:
    10% of average (out of 100) of the 3 auto-graded assignments in weeks 7,9 and 11.
    15% of average (out of 100) of best 8 of the 12 programming assignments.
  • Also since the focus of the course apart from dealing with basics of image processing is also to help you learn how to implement the various techniques, the final exam of 75 marks will be calculated as follows:The in person proctored exam taken at centres will contribute 75 of the total 100 final marks.We will also conduct a 1 hr timed non-proctored programming exam.
This will be for 15 marks.We will add this to the Proctored exam score, capping it at 75.


  • If any one of the 3 criteria is not met, you will not be eligible for the certificate even if the Final score >= 40/100.

    • Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras. It will be e-verifiable at nptel.ac.in/noc.
    •Only the e-certificate will be made available. Hard copies will not be dispatched.

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