2D Frequency Domain Filtering and the 2D DFT
Project Information
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The 2D DFT:
o The Transforms
o Frequency Content Location
o Properties of 2D DFT
o Examples of Properties

Frequency Domain Image Filters:
o 2D Filtering Concepts
o Smoothing
o Edge Detection
o Sharpening
o Filter Design



Group Members

Edge Detection Through High and Bandpass Filters Brought to you by Team Phantom Cruiser and the Power of Steam

Top: Original image. Center: Image filtered with 5th order Butterworth highpass filter, normalized cutoff frequency .5 Bottom: Image filtered with 27th order Butterworth bandpass filter, normalized passband .2 - .8.
Left: Bandpass filter. Right: Highpass filter.

If only keeping the low frequencies discards the edges of the image, then attenuating the low frequencies should only keep the edges. This is exactly what we find when we apply the above highpass filter to the image. The filtered image only keeps the edges of sharpest contrast, such as the curvature around the headlights, the edges of the windshield, and the space around the doors.

A somewhat more complete view of the car is given by the results of the bandpass filter. This ignores the very high frequency noise in the image, and brings out most areas in which a change occurs. This allows it to find not only edges but faster gradients, such as the ones hidden in the dark grille on the front of the car, and the pockets in the hubcaps.