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<html>
<head>
<title>
IMAGE_DIFFUSE - Black/White Version of Grayscale Image
</title>
</head>
<body bgcolor="#EEEEEE" link="#CC0000" alink="#FF3300" vlink="#000055">
<h1 align = "center">
IMAGE_DIFFUSE <br> Black/White Version of Grayscale Image
</h1>
<hr>
<p>
<b>IMAGE_DIFFUSE</b>
is a MATLAB function which
uses diffusion to smooth the colors in a picture.
</p>
<h3 align = "center">
Usage:
</h3>
<p>
<blockquote>
function <i>g2</i> = <b>image_diffuse</b> ( <i>g</i>, <i>c</i>, <i>k</i> )
</blockquote>
where
<ul>
<li>
<i>g</i> is an <i>m</i> by <i>n</i> <b>uint8</b>
(short integers, 0 to 255) array containing the grayscale image data;
MATLAB's <b>imread()</b> command can be used to create such a
dataset from a graphics image file.
</li>
<li>
<i>c</i> is a value, typically between 0 and 1, which controls the
diffusion. C = 0 means the picture is unchanged. C = 1 means each
pixel is completely replaced by a neighborhood average.
</li>
<li>
<i>k</i> indicates the number of steps of diffusion to carry out.
After k steps, a single black pixel will be diffused with pixels
up to k pixels away in all directions.
</li>
<li>
<i>g2</i> is an <i>m</i> by <i>n</i> <b>uint8</b>
array containing the diffused version of the image.
</li>
</ul>
</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_DIFFUSE</b> is available in
<a href = "../../m_src/image_diffuse/image_diffuse.html">a MATLAB version</a>.
</p>
<h3 align = "center">
Related Data and Programs:
</h3>
<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>,
a MATLAB library which
applies image processing techniques to remove noise from an image.
</p>
<p>
<a href = "../../m_src/image_edge/image_edge.html">
IMAGE_EDGE</a>,
a MATLAB program which
demonstrates a simple technique for edge detection in an image.
</p>
<p>
<a href = "../../m_src/image_match_genetic/image_match_genetic.html">
IMAGE_MATCH_GENETIC</a>,
a MATLAB program which
tries to match a 256x256 JPEG image by blending 32 colored rectangles,
using ideas from genetic algorithms,
based on an example by Nick Berry.
</p>
<p>
<a href = "../../m_src/image_noise/image_noise.html">
IMAGE_NOISE</a>,
a MATLAB library which
adds noise to an image.
</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>,
a MATLAB function which
creates a grayscale version of an RGB image.
</p>
<p>
<a href = "../../m_src/image_threshold/image_threshold.html">
IMAGE_THRESHOLD</a>,
a MATLAB library which
makes 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 = "image_diffuse.m">image_diffuse.m</a>,
applies diffusion to a gray scale image.
</li>
</ul>
</p>
<h3 align = "center">
Examples and Tests:
</h3>
<p>
<b>FOOL</b> is an image which was originally a true black and white image;
that is, as a gray scale image, every pixel was set to 0 or 255.
<ul>
<li>
<a href = "fool.png">fool.png</a>,
the original image.
</li>
<li>
<a href = "fool_c0.05_k20.png">fool_c0.05_k20.png</a>,
the result for C = 0.05, K = 20;
</li>
<li>
<a href = "fool_c0.50_k01.png">fool_c0.50_k01.png</a>,
the result for C = 0.50, K = 1.
</li>
<li>
<a href = "fool_c0.50_k20.png">fool_c0.50_k20.png</a>,
the result for C = 0.50, K = 20.
</li>
<li>
<a href = "fool_c1.00_k01.png">fool_c1.00_k01.png</a>,
the result for C = 1.00, K = 1
</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 22 July 2011.
</i>
<!-- John Burkardt -->
</body>
</html>