CP467 - Filtering

0.0(0)
studied byStudied by 0 people
learnLearn
examPractice Test
spaced repetitionSpaced Repetition
heart puzzleMatch
flashcardsFlashcards
Card Sorting

1/15

encourage image

There's no tags or description

Looks like no tags are added yet.

Study Analytics
Name
Mastery
Learn
Test
Matching
Spaced

No study sessions yet.

16 Terms

1
New cards

What are alternate names for filters?

Masks, kernels , templates and windows

2
New cards

What are the two parts of a spatial filter?

1. A neighbourhood
2. A predefined operation

3
New cards

What is spatial correlation?

The process of moving a filter mask over the image and computing the sum of products at each location

4
New cards

What is spatial convolution?

The same as spatial correlation expect the filter is rotated by 180 degrees.

5
New cards

What are smoothing filters used for?

Blurring an image (commonly used for noise reduction)

6
New cards

What is the output of a smoothing linear spatial filter?

The average of the pixels contained in the neighbourhood

7
New cards

What is the best example of a order statistics (nonlinear) filter?

A median filter

8
New cards

What are median filters good for?

They are effective with dealing with impulse noise (also known as salt and pepper noise)

9
New cards

What is the objective of a sharpening spatial filter?

Highlighting fine details in an image or enchanting details that have been blurred.

10
New cards

How is sharpening accomplished?

Spatial differentiation

11
New cards

Requirements for any definition we use for a first derivative?

1. Must be zero in flat segments
2. Must be nonzero at the onset of a gray-level or ramp
3. Must be nonzero along ramps

12
New cards

Requirements for any definition we use for a second derivative?

1. Must be not zero in flat areas
2. Must be nonzero at the onset and end of a gray-level step or ramp
3. Must be zero along ramps of constant slope

13
New cards

What are the most used gradient masks?

1. Prewitt
2. Sobel

14
New cards

What does Laplacian produce?

Produces images with grayish edge lines superimposed on a dark background

15
New cards

What is unsharp masking?

Getting a sharpened image by subtracting a smoothed version of the image from the original one

16
New cards

What are the 3 steps for unsharp masking?

1. Blur original image
2. Subtract the blurred image from the original one
3. Add the mask to the original