Video Analytics Class 2

My Notes

• Linear Filter - Linear combination of neighbours
• Box filter - All values constant [1's]
• Corr-relation - Masked and Moved across Image
• Gradient  - due to surface normal discontinuity, depth discontinuity, illumination discontinuity
• LOG - Laplace of Gaussian. LOG capable of finding edges
• Salt and Pepper Image - Image has random black and white 

Basics

• Represent Image as a Matrix
• Represent Image as a function
• Point, local operations, histogram equalization, moving average model
• Cross Correlation g = H X F
• Gaussian filter (Removes High frequency, blurring, smoothens image)
• Symmetric Matrix (When you shift rows into columns it would appear the same ( aij = aji, for all indices i and j) example link 

Convolution Basics

Programmatic Walkthru - link

From link 

From link

From Link
FFT

Convolution Applications

• Smoother image
• Gaussian (Point spread function)
• Different Kinds of filter (Box, Gaussian filter)

Cross Correlation - Assess how similar are two different functions. Compares position by position. 

Correlation Walkthru

From Link 

Mathematics concepts to learn

• Vector Product
• Eigen Value decomposition
• First Derivative, Second Derivative

Vertical and horizontal edge detection filters - Sobel, Roberts, Prewitt (Veritical, Horizontal, Diagonal edge detection filters).

Good Read Link
MIT Course Slides link

Related Reads







Happy Learning!!!