Digital Image Processing
Lecture10: MATLAB Example –
Utility M-functions for Intensity
Transformations
Handling a variable number of
inputs and/or outputs
• To check the number of arguments into an
M-function we use function nargin.
n = nargin
which returns the actual number of
arguments input into the M-function.
Similarly, function nargout is used in
connection with the outputs of an Mfunction. The syntax is:
n = nargout
Handling a variable number of
inputs and/or outputs
• For example, suppose that we execute the
following M-function at the prompt:
>> T = testhv(4,5);
Use of nargin within the body of this function
would return a 2, while use of nargout would
return 1.
Handling a variable number of
inputs and/or outputs
• Function nargchk can be used in the body of an
M-function to check if the correct number of
arguments were passed. The syntax is:
msg = nargchk (low, high, number)
This function returns the message “Not enough
input parameters” if number is less than low, or
“Two many input parameters” if number is
greater than high. If number is between low and
high, nargchk returns an empty matrix.
Handling a variable number of
inputs and/or outputs
• A frequent use of function nargchk is to stop execution via the error
function if the incorrect number of arguments is input. The number of
actual arguments is determined by the nargin function.
• For example, consider the following code fragment:
function G = test (x, y, z)
….
error (nargchk (2,3, nargin)
…
now, when typing:
>> test (6);
Which has only one input argument would produce the error.
“Not enough input arguments” and execution would terminate.
Handling a variable number of
inputs and/or outputs
• Often it is useful to be able to write functions in which the number of
input and/or output arguments is variable. For this we use the
variables varargin and varargout. For example:
function [m, n] = test (varargin)
accepts a variable number of inputs into function test, and
function [varargout] = test (m, n, p)
returns a variable number of outputs from function test. If function
test had, say, one fixed input argument, x, followed by a variable
number of input arguments, then
function [m, n] = test (x, varargin)
would cause varargin to start with the second input argument
supplied by the user when the function is called.
Handling a variable number of
inputs and/or outputs
• It is acceptable to have a function in which both the number of input
and output arguments is variable.
• When varargin is used as the input argument of a function,
MATLAB sets it to a cell array (def. A cell array is a datatype with
index data containers called cells. Each cell can contain any type of
data. Cell array commonly contain lists of text strings, combination
of text and numbers or numeric arrays of different sizes) that
accepts a variable number of inputs by the user.
• Because varargin is a cell array, an important aspect of this
arrangement is that the call to the function can contain a mixed set
of inputs. For example, we can call test function as follows:
>> [m, n] = test (f, [0 0.5 1.5], A, ‘label’);
Handling a variable number of
inputs and/or outputs
• where f is an image, the next argument is a row vector of length 3, A
is a matrix, and ‘label’ is a character string. This is indeed a
powerful feature that can be used to simplify the structure of
functions requiring a variety of different inputs. Similar comments
apply to varargout.
An M-function for intensity
transformation
• In this section, we develop a function that computes
the following transformation functions: negative, log,
gamma and contrast stretching.
• In writing this function we use function changeclass,
which has the syntax
g = changeclass (newclass, f)
This function converts image f to the class specified in
parameter newclass and outputs it as g. Valid values
for newclass are ‘uint8’, ‘uin16’ and ‘double’
An M-function for intensity
transformation
function image = changeclass (class, varargin)
%CHANGECLASS changes the storage class of an image
% I2 = CHANGECLASS(CLASS, I);
% RGB2 = CHANGECLASS(CLASS, RGB);
% BW2 = CHANGECLASS(CLASS, BW);
% X2 = CHANGECLASS(CLASS, X, 'indexed');
% Copyright 1993-2002 The MathWorks, Inc. Used with permission.
switch class
case 'uint8'
image = im2uint8 (varargin{:});
case 'uint16'
image = im2uint16 (varargin {:});
case 'double'
image = im2double(varargin {:});
otherwise
error ('Unsupported IPT data class');
end
An M-function for intensity
transformation
• Note in the following M-function, which we call intrans,
how function operations are formatted in the Help
section of the code, how a variable number of inputs is
handled, how error checking is interleaved in the code,
and how the class of the output image is matched to
the class of the input. Keep in mind when studying the
following code that varargin is a cell array, so its
elements are selected by using curly brackets {}.
An M-function for intensity
transformation
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function g = intrans (f, varargin)
%INTRANS performs intensity (gray-level) transformations.
% G = INTRANS (F, 'neg') computes the negative of input image F.
%
% G = INTRANS(F, 'log', C, CLASS) computes C*log(1+F) and multiplies
% the result by (positive) constant C. If the last two parameters are
% omitted, C defaults to 1. Parameter CLASS offers the option to specify
% the class of the output as 'uint8' or 'uint16'. if parameter CLASS is
% omitted, the output is of the same class as the input.
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% G = INTRANS(F, 'gamma', GAM) performs a gamma transformation on
the
% input image using parameter GAM (a required input).
An M-function for intensity
transformation
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G = INTRANS(F, 'stretch', M, E) computes a contrast-stretching
transformation using the expression 1./(1+ (M./(F + eps)).^E).
Parameter M must be in the range [0 1]. the default value for M is
mean2 (im2double(F)), and the default value for E is 4
For the 'neg', 'gamma' and 'stretch' transformations, double input
images whose maximum value is greater than 1 are scaled first using
MAT2GRAY. Other images are converted to double first using
IM2DOUBLE.
% for the 'log' transformation, double images are transfortmed without
% being scaled;
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% the output is of the same class as the input, except if a different
% class is specified for the 'log' option.
An M-function for intensity
transformation
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% Verify the correct number of inputs
error (nargchk (2, 4, nargin)
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% Store the class of the input for use later.
classin = class (f);
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% If the input is of class double, and it is outside the range
% [0 1], and the specified transformation is not 'log', convert the
% input to the range [0 1].
if strcmp(class(f), 'double') & max(f(:)) > 1 & ...
- strcmp(varargin{1}, 'log')
f = mat2gray(f);
else % Convert to double, regardless of class (f)
f = im2double(f);
end
An M-function for intensity
transformation
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% Determine the type of transformation specified.
method = varargin {1};
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% Perform the intensity transformation specified.
switch method
case 'neg'
g = imcompelment (f);
An M-function for intensity
transformation
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case 'log'
if length(varargin) == 1
c = 1;
elseif length(varargin) == 2
c = varargin{2};
elseif length(varargin) == 3
c = varargin {2};
classin = varargin{3};
else
error ('Incorrect number of inputs for the log option')
end
g = c*(log(1 + double(f)));
An M-function for intensity
transformation
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case 'gamma'
if length(varargin) < 2
error ('Not enough inputs for the gamma option')
end
gam = varargin {2};
g = imadjust (f, [ ], [ ], gam);
An M-function for intensity
transformation
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case 'stretch'
if length(varargin) == 1
% Use defaults.
m = mean2(f);
E = 4.0;
elseif length(varargin) == 3
m = varargin {2};
E = varargin {3};
else
error ('Incorrect number of inputs for the stretch option.')
end
g = 1./(1 + (m./(f + eps)).^E);
otherwise
error ('Unknown enhancement method')
end
An M-function for intensity
transformation
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% Convert to the class of the input image.
g = changeclass (classin, g);