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25 lines
1.3 KiB
Plaintext
25 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 neightornood
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Operation in which each output pixel is the weighted sum of neighboring input pixels. The matrix of weights is called the
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convolution kemel, also known as the filter. A convolution kemel is a correlation kernel that has been rotated 120 cegre
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For example, suppose the image is
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= [17 24 1 8 15
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235 7 14 16
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4 6 13 20 22
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1@ 12 19 21 3
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