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            <c val="#008080">IMAGE MANIPULATION</c>
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              <c val="#800080">Addition and Measurement of Noise</c>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">This function adds random (salt-and-pepper) noise of a given intensity to an existing image. Noise is added to images to simulate distortion, or to demonstrate the effectiveness of particular types of filters.</p>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">The function returns an image matrix that contains the specified intensity transformation.</p>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">This function adds or subtracts noise of magnitude <f family="Times New Roman" charset="0"><inlineAttr font-weight="normal" line-through="false">n (where n is any real number) to each element of M with probability p/2. The noise has equal probability of being added or subtracted (total probability p of either). T</inlineAttr></f>he function also clips the resulting noisy image from 0 to 255.</p>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">To see the effect of the noise mathematically, look at the difference between the histograms of the two images:</p>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">You can see the large spikes of difference at 0 and 255 resulting from the clipping performed by the<b> addnoise</b> function.</p>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">We could also look at the correlation between the noisy and the original image. The images are still highly correlated in their intensity levels. Try changing the values of p and n to see how the two-dimensional histogram is affected.</p>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">You can generate other types of noise in <f family="Times New Roman" charset="0"><inlineAttr font-weight="normal" line-through="false">Mathcad</inlineAttr></f> using the functions at your disposal. For example, to generate Gaussian noise use the following:</p>
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        <p style="Normal" margin-left="0" margin-right="0" text-indent="0" text-align="left" list-style-type="none" tabs="inherit">where <f family="Times New Roman" charset="0"><inlineAttr font-weight="normal" line-through="false">A</inlineAttr></f><b><sp /></b>is the mean value of the noise, and <f family="Symbol" charset="2"><inlineAttr font-weight="normal" line-through="false">s</inlineAttr></f> is the standard deviation. You might apply this noise by generating a noise matrix and adding it to the image: </p>
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