What Is Image Filtering in the Spatial Domain?                            |

Filtering is a technique for modifying or enhancing an image. For example, you can filter an image to emphasize certain
features or remove other features. Image processing operations implemented with filtering include smoothing, sharpening,
and edge enhancement.

Filtering is a neighborhood operation, in which the value of any given pixel in the output image is determined by applying
some algorithm to the values of the pixels in the neighborhood of the corresponding input pixel. A pixel's neighborhood is
some set of pixels, defined by their locations relative to that pixel. (SeeNeighborhood or Block Processing: An Overview for
a general discussion of neighborhood operations.) Linear filtering is filtering in which the value of an output pixel is a linear
combination of the values of the pixels in the input pixel's neighborhood.

Convolution

Linear filtering of an image is accomplished through an operation called convolution. Convolution is a neightornood
Operation in which each output pixel is the weighted sum of neighboring input pixels. The matrix of weights is called the
convolution kemel, also known as the filter. A convolution kemel is a correlation kernel that has been rotated 120 cegre

For example, suppose the image is

= [17 24 1 8 15
235 7 14 16
4 6 13 20 22
1@ 12 19 21 3