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Questions and Answers
What is the primary advantage of adaptive median filtering over median filtering?
What are the three main purposes of the adaptive median filter?
What is the key insight in the adaptive median filter?
What is the difference between the median filter and the average filter?
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What is the primary goal of the adaptive median filter in terms of noise reduction?
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What is the purpose of the level B in the adaptive median filter algorithm?
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What type of noise is typically removed by a max filter?
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What is the primary advantage of an adaptive filter over a fixed filter?
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What is the purpose of the alpha-trimmed mean filter?
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What is the main difference between a median filter and an average filter?
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What is the effect of applying a 3x3 max filter to an image corrupted by pepper noise?
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What is the primary application of a median filter?
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What is the purpose of using spatial filters in image processing?
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What is the main difference between the arithmetic mean filter and the geometric mean filter?
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Which type of filter is suitable for removing impulse noise in an image?
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What is the advantage of using an adaptive median filter over a non-adaptive median filter?
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What is the formula for the arithmetic mean filter?
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Which type of filter is more suitable for image smoothing, the median filter or the arithmetic mean filter?
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Study Notes
Adaptive Median Filtering
- The adaptive median filter can handle spatially dense impulse noise and performs some smoothing for non-impulse noise.
- The filter size changes depending on the characteristics of the image.
- The algorithm has three purposes: remove impulse noise, provide smoothing of other noise, and reduce distortion.
Notation
- zmin: minimum grey level in Sxy
- zmax: maximum grey level in Sxy
- zmed: median of grey levels in Sxy
- zxy: grey level at coordinates (x, y)
- Smax: maximum allowed size of Sxy
Level A
- A1 = zmed - zmin
- A2 = zmed - zmax
- If A1 > 0 and A2 < 0, Go to level B
- Else increase the window size
- If window size ≤ Smax, repeat Level A
- Else output zmed
Level B
- B1 = zxy - zmin
- B2 = zxy - zmax
- If B1 > 0 and B2 < 0, output zxy
- Else output zmed
Median Filter and Adaptive Median Filter
- Examples: Salt and pepper noise, MRI brain images
- Median filter results: remove impulse noise
- Adaptive median filter results: handle spatially dense impulse noise and provide smoothing
Other Filters
- Max and Min Filters: example, Image corrupted by pepper noise with prob.= 0.1
- Alpha-trimmed Mean Filter: formula, example, Image corrupted by additive uniform noise and salt-and-pepper noise
- Adaptive Filter: general concept, more complex, superior performance, adaptive, local noise reduction filter
Mean Filters
- Degradation model: g(x, y) = f(x, y) * h(x, y) + η(x, y)
- Arithmetic mean filter or moving average filter
- Geometric mean filter: formula
- Harmonic mean filter, Contraharmonic mean filter
Order-Statistic Filters
- Median filter
- Max and min filters
- Midpoint filter
- Alpha-trimmed mean filter
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Description
Learn about the adaptive median filter and its ability to handle spatially dense impulse noise. Discover how the filter size changes depending on image characteristics.
