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<html>
<head>
<title>
IMAGE_NOISE - Add Noise to an Image
</title>
</head>
<body bgcolor="#EEEEEE" link="#CC0000" alink="#FF3300" vlink="#000055">
<h1 align = "center">
IMAGE_NOISE <br> Add Noise to an Image
</h1>
<hr>
<p>
<b>IMAGE_NOISE</b>
is a directory of MATLAB programs which
add noise to an image.
</p>
<p>
In MATLAB, a black and white or gray scale image can be represented
using a 2D array of nonnegative integers over some range 0 to GMAX.
The value 0 indicates black, and GMAX white. Intermediate values
represent shades of gray in a natural way. Note, however, that
the eye has a nonlinear response to intensity, so that the value
GMAX/2 will not be perceived as halfway between 0 and GMAX. That
is a separate issue.
</p>
<p>
A color image can be represented using a set of 3 2D arrays,
which can be thought of as R, G, and B, and which represent the
intensity of the red, green and blue signals that combine to
form the color image. A common maximum value is assumed, RGBMAX.
</p>
<p>
An image can be read into MATLAB using the <b>imread</b> function
in the Image Processing Toolbox, and displayed with the <b>imshow</b>
function.
</p>
<p>
A simple model for noise involves replacing a subset of the image
pixels by the extreme low or high values. In a grayscale image,
the damaged pixels show up as black or white spots, giving this kind
of noise the name "salt and pepper". An RGB image may be damaged
by resetting all 3 color values at a given pixel, resulting in
white or black pixels; however, a more realistic noise damage would
simply choose R, G or B values randomly, so that noisy pixels would
show up as those with full or zero value in one color channel, looking
as though colored confetti had been tossed onto the image.
</p>
<p>
More sophisticated models of noise damage involve setting a pixel
color value to a uniform or normal random value, or to displacing
the pixel color value by a uniform or normal random value.
</p>
<h3 align = "center">
Licensing:
</h3>
<p>
The computer code and data files described and made available on this web page
are distributed under
<a href = "../../txt/gnu_lgpl.txt">the GNU LGPL license.</a>
</p>
<h3 align = "center">
Languages:
</h3>
<p>
<b>IMAGE_NOISE</b> is available in
<a href = "../../m_src/image_noise/image_noise.html">a MATLAB version</a>.
</p>
<h3 align = "center">
Related Data and Programs:
</h3>
<p>
<a href = "../../m_src/image_components/image_components.html">
IMAGE_COMPONENTS</a>,
a MATLAB library which
seeks the connected "nonzero" or "nonblack" components of an image or integer vector,
array or 3D block.
</p>
<p>
<a href = "../../m_src/image_contrast/image_contrast.html">
IMAGE_CONTRAST</a>,
a MATLAB program which
applies image processing techniques to increase the contrast in an image.
</p>
<p>
<a href = "../../m_src/image_denoise/image_denoise.html">
IMAGE_DENOISE</a>,
MATLAB programs which
apply image processing techniques to remove noise from an image.
</p>
<p>
<a href = "../../m_src/image_diffuse/image_diffuse.html">
IMAGE_DIFFUSE</a>,
a MATLAB library which
uses diffusion to smooth out an image.
</p>
<p>
<a href = "../../m_src/image_edge/image_edge.html">
IMAGE_EDGE</a>,
a MATLAB library which
demonstrates a simple procedure for edge detection in images.
</p>
<p>
<a href = "../../m_src/image_quantization/image_quantization.html">
IMAGE_QUANTIZATION</a>,
a MATLAB library which
demonstrates how the KMEANS algorithm can be used to reduce the number
of colors or shades of gray in an image.
</p>
<p>
<a href = "../../m_src/image_rgb_to_gray/image_rgb_to_gray.html">
IMAGE_RGB_TO_GRAY</a>,
MATLAB programs which
makes a grayscale version of an RGB image.
</p>
<p>
<a href = "../../m_src/image_threshold/image_threshold.html">
IMAGE_THRESHOLD</a>,
MATLAB programs which
make a black and white version of a grayscale image by setting all pixels
below or above a threshold value to black or white.
</p>
<h3 align = "center">
Reference:
</h3>
<p>
MathWorks documentation for the Image Processing Toolbox is available at
<a href = "http://www.mathworks.com/access/helpdesk/help/pdf_doc/images/images_tb.pdf">
http://www.mathworks.com/access/helpdesk/help/pdf_doc/images/images_tb.pdf</a>.
</p>
<p>
<ul>
<li>
Jonas Gomes, Luiz Velho,<br>
Image Processing for Computer Graphics,<br>
Springer, 1997,<br>
ISBN: 0387948546,<br>
LC: T385.G65.
</li>
<li>
William Pratt,<br>
Digital Image Processing,<br>
Second Edition,<br>
Wiley, 1991,<br>
ISBN13: 978-0471857662,<br>
LC: TA1632.P7.
</li>
</ul>
</p>
<h3 align = "center">
Source Code:
</h3>
<p>
<ul>
<li>
<a href = "gray_salt_and_pepper.m">gray_salt_and_pepper.m</a>,
adds salt and pepper noise to a grayscale image.
</li>
<li>
<a href = "rgb_salt_and_pepper.m">rgb_salt_and_pepper.m</a>,
adds salt and pepper noise to a grayscale image.
</li>
</ul>
</p>
<h3 align = "center">
Examples and Tests:
</h3>
<p>
<b>MILKING</b> is an RGB image of a cow being milked.
<ul>
<li>
<a href = "milking.png">milking.png</a>,
the original image.
</li>
<li>
<a href = "milking_05.png">milking_05.png</a>,
the image with 5% salt and pepper noise.
</li>
<li>
<a href = "milking_10.png">milking_10.png</a>,
the image with 10% salt and pepper noise.
</li>
<li>
<a href = "milking_20.png">milking_20.png</a>,
the image with 20% salt and pepper noise.
</li>
<li>
<a href = "milking_40.png">milking_40.png</a>,
the image with 40% salt and pepper noise.
</li>
<li>
<a href = "milking_60.png">milking_60.png</a>,
the image with 60% salt and pepper noise.
</li>
<li>
<a href = "milking_80.png">milking_80.png</a>,
the image with 80% salt and pepper noise.
</li>
</ul>
</p>
<p>
<b>PIONEERS</b> is a grayscale image of two boys.
<ul>
<li>
<a href = "pioneers.png">pioneers.png</a>,
the original image.
</li>
<li>
<a href = "pioneers_05.png">pioneers_05.png</a>,
the image with 5% salt and pepper noise.
</li>
<li>
<a href = "pioneers_10.png">pioneers_10.png</a>,
the image with 10% salt and pepper noise.
</li>
<li>
<a href = "pioneers_20.png">pioneers_20.png</a>,
the image with 20% salt and pepper noise.
</li>
<li>
<a href = "pioneers_40.png">pioneers_40.png</a>,
the image with 40% salt and pepper noise.
</li>
<li>
<a href = "pioneers_60.png">pioneers_60.png</a>,
the image with 60% salt and pepper noise.
</li>
<li>
<a href = "pioneers_80.png">pioneers_80.png</a>,
the image with 80% salt and pepper noise.
</li>
</ul>
</p>
<p>
You can go up one level to <a href = "../m_src.html">
the MATLAB source codes</a>.
</p>
<hr>
<i>
Last revised on 26 February 2011.
</i>
<!-- John Burkardt -->
</body>
</html>