04-02-2013, 12:50 PM
Neighborhood Operations
1Neighborhood Operations.ppt (Size: 4.42 MB / Downloads: 123)
Objectives
Why are neighborhoods important?
What is linear convolution?
discrete
templates, masks or filters
algorithm mechanics
graphical interpretation
Describe non-linear operators
maximum
minimum
median
What is tiling?
Convolution versus Spectral
We learnt two methods of processing images:
Convolution
Spectral
We analyzed and demonstrated how to build a processor (systolic, pipelined, parallel, cellular automaton) for 1D convolution.
1D convolution is used in speech processing and in polynomial multiplication.
We will use visualized animations now to show in more detail how 2D convolution works for images.
This should convince you how important it is to do convolution quickly in modern Spectral Architectures, especially for 3D etc.
2D Convolution
Consists of filtering an image A using a filter (mask, template) B.
Mask is a small image whose pixel values are called weights.
Weights modify relationships between pixels.