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19 Cards in this Set
- Front
- Back
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Algorithms are fundamental to digital image processing. These operations can be divided into four categories:
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▫ operations based on the image histogram,
▫ on simple mathematics, ▫ on convolution, and ▫ on mathematical morphology. |
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what are the two types of filters?
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linear and non-linear filters
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What is meant by Linear Filters?
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Filtering in which the value of an output
pixel is a linear combination of the values of the pixels in the input pixel’s neighbourhood. ▫ Accomplished through technique called Convolution. |
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What is Convolution in Processing
Images? |
▫ Technique of computing the value of an
output pixel as a weighted sum of its neighbouring pixels. ▫ Matrix of weights is called the Convolution Kernel or Filter. |
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How is Convolution done?
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1. Slide centre element of
kernel to top of computing element of A. 2. Multiply each weight in the rotated kernel by the pixel of A. 3. Sum up the individual product in above step. 4. Prescribe onto target pixel |
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convolution
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eg
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eg of a 3X3 mean kernel
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Often a 3×3 square convolution kernel is used although sometimes
5x5 square kernel is also used. |
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what does the mean filter do?
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Smoothes images by reducing the amount of intensity variation
between one pixel and the next. (▫ Smoothing an image not only reduce the noise, but also the finescaled image details because they also blocked high frequencies) |
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mean filters make the images more ____.
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blurry
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What does a median filter do?
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• Medial Filter preserves useful detail in the image
• Median filter is a nonlinear filter. ▫ Median is calculated by first sorting all the pixel values. ▫ Centre pixel is replaced with the median, or centre value present among its neighbours |
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A common way to reduce noise is _______.
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averaging
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• Low pass filtering can suppress _____.
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noise
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High pass filtering can enhance ______.
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detail
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Noise smoothing is _____
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(low pass)
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Elimination of image defects (artifacts) by using _____.
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(median filtering)
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Edge detection is a _____-.
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(high pass, derivative filters)
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Image enhancement (image restoration) is a ________.
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(high boost filtering)
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• One example of non-linear spatial filters is a ______filter it is good for removing impulse noise from
images |
median
filter |
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How does the median filter work?
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The filter cleans up images with bright noise spikes, because the
bright pixels tend to end up at the top of the ascending order of pixels in each pixel group • As a result the bright spikes are replaced by the median filter on an image corrupted by impulse noise |
