imfilter - N-D filtering of multidimensional images

Syntax

B = imfilter(A,H)
B = imfilter(A, H, option1, option2,...)

Description

B = imfilter(A,H) filters the multidimensional array A with the multidimensional filter H. The array A can be logical or a nonsparse numeric array of any class and dimension. The result B has the same size and class as A.

Each element of the output B is computed using double-precision floating point. If A is an integer or logical array, then output elements that exceed the range of the integer type are truncated, and fractional values are rounded.

B = imfilter(A, H, option1, option2,...) performs multidimensional filtering according to the specified options. Option arguments can have the following values.

Boundary Options

Option

Description

X

Input array values outside the bounds of the array are implicitly assumed to have the value X. When no boundary option is specified, imfilter uses X = 0.

'symmetric'

Input array values outside the bounds of the array are computed by mirror-reflecting the array across the array border.

'replicate'

Input array values outside the bounds of the array are assumed to equal the nearest array border value.

'circular'

Input array values outside the bounds of the array are computed by implicitly assuming the input array is periodic.

Output Size Options

Option

Description

'same'

The output array is the same size as the input array. This is the default behavior when no output size options are specified.

'full'

The output array is the full filtered result, and so is larger than the input array.

Correlation and Convolution Options

Option

Description

'corr'

imfilter performs multidimensional filtering using correlation, which is the same way that filter2 performs filtering. When no correlation or convolution option is specified, imfilter uses correlation.

'conv'

imfilter performs multidimensional filtering using convolution.

N-D convolution is related to N-D correlation by a reflection of the filter matrix.

Examples

Read a color image into the workspace and view it.

originalRGB = imread('peppers.png');
imshow(originalRGB)

Create a filter, h, that can be used to approximate linear camera motion.

h = fspecial('motion', 50, 45);

Apply the filter, using imfilter, to the image originalRGB to create a new image, filteredRGB.

filteredRGB = imfilter(originalRGB, h);
figure, imshow(filteredRGB)

Note that imfilter is more memory efficient than some other filtering operations in that it outputs an array of the same data type as the input image array. In this example, the output is an array of uint8.

whos
Name               Size                Bytes  Class     Attributes

  filteredRGB      384x512x3            589824  uint8               
  h                 37x37                10952  double              
  originalRGB      384x512x3            589824  uint8         

Specify the replicate boundary option.

boundaryReplicateRGB = imfilter(originalRGB, h, 'replicate');
figure, imshow(boundaryReplicateRGB)

See Also

conv2, convn, filter2, fspecial, ippl

  


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