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23 lines
1.3 KiB
Plaintext
23 lines
1.3 KiB
Plaintext
What is Image Filtering in the Spatial Domain?
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Filtering is a technique for modifying or enhancing an image. For example, you can filter an image to emphasize certain
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features or remove other features. Image processing operations implemented with filtering include smoothing, sharpening,
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and edge enhancement.
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Filtering is a neighborhood operation, in which the value of any given pixel in the output image is determined by applying
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some algorithm to the values of the pixels in the neighborhood of the corresponding input pixel. A pixel's neighborhood is
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some set of pixels defined by their locations relative to that pixel. (SeeNeighborhood or Block Processing: An Overview for
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a general discussion of neighborhood operations.) Linear filtering is filtering in which the value of an output pixel is a linear
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combination of the values of the pixels in the input pixel's neighborhood.
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Convolution
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Linear filtering of an image is accomplished through an operation called convolution. Convolution is a neighborhood
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operation in which each output pixel is the weighted sum of neighboring input pixels. The matrix of wehights is called the
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convolution kernal, also known as the filter. A convolution kernel is a correlation kernel that has been rotated 180 degrees.
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For example, suppose the image is
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A = [17 24 1 8 15
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23 5 7 14 16
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4 6 13 20 22
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10 12 19 21 3 |