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September 25, 2023

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Description

Image Signal Processing. Instructor: Prof. A. N. Rajagopalan, Department of Electrical and Electronics Engineering, IIT Madras.

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. (from nptel.ac.in)

Course Curriculum

  • Lecture 01 – Course Introduction Unlimited
  • Lecture 02 – Applications of Image Processing Unlimited
  • Lecture 03 – Applications of Image Processing (cont.) Unlimited
  • Lecture 04 – Basics of Images Unlimited
  • Lecture 05 – Shot Noise Unlimited
  • Lecture 06 – Geometric Transformations Unlimited
  • Lecture 07 – Geometric Transformations (cont.) Unlimited
  • Lecture 08 – Bilinear Interpolation Unlimited
  • Lecture 09 – Geometric Transformations (cont.) Unlimited
  • Lecture 10 – Projective Transformation Unlimited
  • Lecture 11 – Homography Unlimited
  • Lecture 12 – Homography: Special Cases Unlimited
  • Lecture 13 – Computing Homography Unlimited
  • Lecture 14 – RANSAC Unlimited
  • Lecture 15 – Rotational Homography Unlimited
  • Lecture 16 – Research Challenges Unlimited
  • Lecture 17 – Real Aperture Camera Unlimited
  • Lecture 18 – Real Aperture Camera: Introduction Unlimited
  • Lecture 19 – Circle of Confusion Unlimited
  • Lecture 20 – Depth of Field, Linearity Unlimited
  • Lecture 21 – Space Invariance Unlimited
  • Lecture 22 – 2D Convolution Unlimited
  • Lecture 23 – 2D Convolution (cont.) Unlimited
  • Lecture 24 – Blur Models Unlimited
  • Lecture 25 – Space-Variant Blurring Unlimited
  • Lecture 26 – Shape from X: Introduction Unlimited
  • Lecture 27 – 2-View Stereo Unlimited
  • Lecture 28 – Introduction to Shape from Focus Unlimited
  • Lecture 29 – SFF Principle Unlimited
  • Lecture 30 – Shape from Focus: Gaussian Fitting Unlimited
  • Lecture 31 – Shape from Focus: Focus Operators Unlimited
  • Lecture 32 – Shape from Focus: Examples Unlimited
  • Lecture 33 – Shape from Focus: Tensor Voting Unlimited
  • Lecture 34 – DFD Principle Unlimited
  • Lecture 35 – Motion Blur Unlimited
  • Lecture 36 – Image Transforms: Introduction Unlimited
  • Lecture 37 – Image Transforms: Motivation Unlimited
  • Lecture 38 – 1D Unitary Transforms: Introduction Unlimited
  • Lecture 39 – Extending 1D Unitary Transforms to 2D: Motivation Unlimited
  • Lecture 40 – Extending 1D Unitary Transforms to 2D: Example Unlimited
  • Lecture 41 – Alternative Forms of 2D Unlimited
  • Lecture 42 – Kronecker Product Unlimited
  • Lecture 43 – Kronecker Product (Example Revisited) Unlimited
  • Lecture 44 – Extending 1D Unitary Transforms to 2D: Summary Unlimited
  • Lecture 45 – 1D DFT to 2D DFT Unlimited
  • Lecture 46 – 2D DFT Visualization Unlimited
  • Lecture 47 – 2D DFT Computation Unlimited
  • Lecture 48 – 1D DCT: Definition, Motivation Unlimited
  • Lecture 49 – Relation to DFT Unlimited
  • Lecture 50 – 2D DCT and Walsh-Hadamard Transform Unlimited
  • Lecture 51 – Data Dependent Transforms, Karhunen Loeve Transform Unlimited
  • Lecture 52 – Karhunen Loeve Transform: Concept Unlimited
  • Lecture 53 – Karhunen Loeve Transform: Applications Unlimited
  • Lecture 54 – Karhunen Loeve Transform: Applications (cont.) Unlimited
  • Lecture 55 – Singular Value Decomposition (SVD) Unlimited
  • Lecture 56 – Applications of Singular Value Decomposition (SVD) Unlimited
  • Lecture 57 – Change Detection Unlimited
  • Lecture 58 – Image Thresholding Unlimited
  • Lecture 59 – Adaptive Local Thresholding: Motivation Unlimited
  • Lecture 60 – Chow-Kaneko Local Thresholding Unlimited
  • Lecture 61 – K-Means Method Unlimited
  • Lecture 62 – ISODATA Method Unlimited
  • Lecture 63 – Theory of Histogram Equalization and Modification Unlimited
  • Lecture 64 – Histogram Equalization Example Unlimited
  • Lecture 65 – Image Sequence and Single Image Filtering in Gaussian Noise Unlimited
  • Lecture 66 – Non-Local Means Method Unlimited
  • Lecture 67 – Non-Local Means Filtering (Examples) Unlimited
  • Lecture 68 – Impulse Noise Generator Unlimited
  • Lecture 69 – Impulse Noise Filtering Unlimited
  • Lecture 70 – Transform Domain Filtering Unlimited
  • Lecture 71 – Illumination Handling Unlimited
  • Lecture 72 – Applications of Restoration, and Image Deblurring Unlimited
  • Lecture 73 – Haddamard’s Conditions and Least Squares Solution Unlimited
  • Lecture 74 – Min-Norm Solution and Norm of Linear Operator Unlimited
  • Lecture 75 – Numerical Stability Analysis Unlimited
  • Lecture 76 – Image Blurring Unlimited
  • Lecture 77 – Tikhonov-Miller Regularization Unlimited
  • Lecture 78 – Conditional Mean as an Estimator Unlimited
  • Lecture 79 – Linear Estimator Unlimited
  • Lecture 80 – Wiener Filter Unlimited
  • Lecture 81 – Fourier Wiener Filter Unlimited
  • Lecture 82 – 1D Superresolution Unlimited
  • Lecture 83 – Superresolution Examples Unlimited

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