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applylut

Neighborhood operations on binary images using lookup tables

applylut is not recommended. Use bwlookup instead.

Syntax

A = applylut(BW,LUT)

Description

A = applylut(BW,LUT) performs a 2-by-2 or 3-by-3 neighborhood operation on binary image BW by using a lookup table (LUT). LUT is either a 16-element or 512-element vector returned by makelut. The vector consists of the output values for all possible 2-by-2 or 3-by-3 neighborhoods.

Class Support

BW can be numeric or logical, and it must be real, two-dimensional, and nonsparse. LUT can be numeric or logical, and it must be a real vector with 16 or 512 elements. If all the elements of LUT are 0 or 1, then A is logical. If all the elements of LUT are integers between 0 and 255, then A is uint8. For all other cases, A is double.

Examples

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Perform Erosion Using a 2-by-2 Neighborhood

Create the LUT.

 lutfun = @(x)(sum(x(:))==4);
 lut    = makelut(lutfun,2);

Read image into the workspace and then apply the LUT to the image. An output pixel is on only if all four of the input pixel's neighborhood pixels are on .

 BW1    = imread('text.png');
 BW2    = applylut(BW1,lut);

Show the original image and the eroded image.

 figure, imshow(BW1);
 figure, imshow(BW2);

More About

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Algorithms

applylut performs a neighborhood operation on a binary image by producing a matrix of indices into lut, and then replacing the indices with the actual values in lut. The specific algorithm used depends on whether you use 2-by-2 or 3-by-3 neighborhoods.

2-by-2 Neighborhoods

For 2-by-2 neighborhoods, length(lut) is 16. There are four pixels in each neighborhood, and two possible states for each pixel, so the total number of permutations is 24 = 16.

To produce the matrix of indices, applylut convolves the binary image BW with this matrix.

8     2
4     1

The resulting convolution contains integer values in the range [0,15]. applylut uses the central part of the convolution, of the same size as BW, and adds 1 to each value to shift the range to [1,16]. It then constructs A by replacing the values in the cells of the index matrix with the values in lut that the indices point to.

3-by-3 Neighborhoods

For 3-by-3 neighborhoods, length(lut) is 512. There are nine pixels in each neighborhood, and two possible states for each pixel, so the total number of permutations is 29 = 512.

To produce the matrix of indices, applylut convolves the binary image BW with this matrix.

256    32     4
128    16     2
 64     8     1

The resulting convolution contains integer values in the range [0,511]. applylut uses the central part of the convolution, of the same size as BW, and adds 1 to each value to shift the range to [1,512]. It then constructs A by replacing the values in the cells of the index matrix with the values in lut that the indices point to.

See Also

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