Image Processing Toolbox User's Guide |

**Lookup Table Operations **

Certain binary image operations can be implemented most easily through lookup tables. A lookup table is a column vector in which each element represents the value to return for one possible combination of pixels in a neighborhood.

You can use the `makelut`

function to create lookup tables for various operations. `makelut`

creates lookup tables for 2-by-2 and 3-by-3 neighborhoods. This figure illustrates these types of neighborhoods. Each neighborhood pixel is indicated by an x, and the center pixel is the one with a circle.

For a 2-by-2 neighborhood, there are 16 possible permutations of the pixels in the neighborhood. Therefore, the lookup table for this operation is a 16-element vector. For a 3-by-3 neighborhood, there are 512 permutations, so the lookup table is a 512-element vector.

Once you create a lookup table, you can use it to perform the desired operation by using the `applylut`

function.

The example below illustrates using lookup table operations to modify an image containing text. You begin by writing a function that returns 1 if three or more pixels in the 3-by-3 neighborhood are 1; otherwise, it returns `0`

. You then call `makelut`

, passing in this function as the first argument, and using the second argument to specify a 3-by-3 lookup table.

`lut`

is returned as a 512-element vector of 1's and 0's. Each value is the output from the function for one of the 512 possible permutations.

You then perform the operation using `applylut`

.

**Image Before and After Applying Lookup Table Operation
**

For information about how `applylut`

maps pixel combinations in the image to entries in the lookup table, see the reference page for `applylut`

.

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