NOC:Image Signal Processing

Lecture 1 - Course Introduction

Lecture 2 - Applications of Image processing

Lecture 3 - Applications of Image processing (Continued...)

Lecture 4 - Basics of Images

Lecture 5 - Shot Noise

Lecture 6 - Geometric Transformations

Lecture 7 - Geometric Transformations (Continued...)

Lecture 8 - Bilinear Interpolation

Lecture 9 - Geometric Transformations (Continued...)

Lecture 10 - Projective Transformation

Lecture 11 - Homography

Lecture 12 - Homography - Special cases

Lecture 13 - Computing Homography

Lecture 14 - RANSAC

Lecture 15 - Rotational Homography

Lecture 16 - Research Challenges

Lecture 17 - Real Aperture Camera

Lecture 18 - Real aperture camera - Introduction

Lecture 19 - Cricle of confusion

Lecture 20 - Depth of field, Linearity

Lecture 21 - Space-Invariance

Lecture 22 - 2D Convolution

Lecture 23 - 2D Convolution

Lecture 24 - Blur Models

Lecture 25 - Space-variant Blurring

Lecture 26 - Shape from X - Introduction

Lecture 27 - 2-View Stereo

Lecture 28 - Introduction to Shape from Focus

Lecture 29 - SFF Principle

Lecture 30 - Shape from focus - Gaussian fitting

Lecture 31 - Shape from focus - Focus operators

Lecture 32 - Shape from Focus - Examples

Lecture 33 - Shape from Focus - Tensor Voting

Lecture 34 - DFD Principle

Lecture 35 - Motion Blur

Lecture 36 - Image Transforms - Introduction

Lecture 37 - Image Transforms - Motivation

Lecture 38 - 1D Unitary Transforms - Introduction

Lecture 39 - Extending 1D Unitary Transform to 2D - Motivation

Lecture 40 - Extending 1D Unitary Transform to 2D - Example

Lecture 41 - Alternative Forms of 2D

Lecture 42 - Kronecker Product

Lecture 43 - Kronecker Product - (Example Revisited)

Lecture 44 - Extending 1D Unitary Transform to 2D - Summary

Lecture 45 - 1D DFT to 2D DFT

Lecture 46 - 2D DFT Visualization

Lecture 47 - 2D DFT - Computation

Lecture 48 - 1D DCT - Definition, Motivation

Lecture 49 - Relation to DFT

Lecture 50 - 2D DCT and Walsh-Haddamard Transform

Lecture 51 - Data Dependent Transforms, Karhunen Loeve Transform

Lecture 52 - Karhunen-Loeve Transform (KLT) - Concept

Lecture 53 - Karhunen-Loeve Transform (KLT) - Applications

Lecture 54 - Karhunen-Loeve Transform (KLT) - Applications

Lecture 55 - Singular Value Decomposition (SVD)

Lecture 56 - Applications of SVD

Lecture 57 - Change detection

Lecture 58 - Image Thresholding

Lecture 59 - Adaptive Local thresholding - Motivation

Lecture 60 - Chow-Kaneko Local thresholding

Lecture 61 - K-Means Method

Lecture 62 - ISODATA Method

Lecture 63 - Theory of Histogram Equalization and Modification

Lecture 64 - Histogram Equalization example

Lecture 65 - Image sequence and Single image filtering in Gaussian noise

Lecture 66 - Non-local Means Method

Lecture 67 - Non-local Means Filtering (Examples)

Lecture 68 - Impulse Noise Generator

Lecture 69 - Impulse noise filtering

Lecture 70 - Transform Domain Filtering

Lecture 71 - Illumination Handling

Lecture 72 - Applications of Restoration, and Image Deblurring

Lecture 73 - Haddamard's conditions and Least squares solution

Lecture 74 - Min-norm solution and Norm of Linear operator

Lecture 75 - Numerical stability analysis

Lecture 76 - Image Deblurring

Lecture 77 - Tikhonov-Miller Regularization

Lecture 78 - Conditional Mean as an Estimator

Lecture 79 - Linear Estimator

Lecture 80 - Wiener Filter

Lecture 81 - Fourier Wiener Filter

Lecture 82 - 1D Superresolution

Lecture 83 - Superresolution Examples