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PORemoving outliers from a grey-scale image
 

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    <h1>Question</h1> <p>I have an images sequence representing depth information which I'd like to clean. There are some outliers (values with intensity below 25, for a 0-255 range) which I would like to be filled with an acceptable alternative (an average value localised to that specific area could be a good guess).</p> <p>Can someone see a simple way to do this? I've tried to use a median filter (filter size of 10) substituting the undesired values with NaN, but it did worsen the situation, which improves instead by substituting them with a general average value.</p> <p><img src="https://i.stack.imgur.com/xwJ6B.png" alt="Basic trial"></p> <p>P.S. Someone has already suggested me to use a <em>fast wavelet reconstruction</em>, but I would not really know where to start...</p> <h1>Implemented solution (so far)</h1> <p>The solution I implemented (before reading about <code>inpaint_nans</code> suggested by <a href="https://stackoverflow.com/users/1214731/tmpearce"><strong>tmpearce</strong></a>) is:</p> <ol> <li>duplicate the original image;</li> <li>filling the invalid pixels with a general average value;</li> <li>use a circular disk of ray 10 for blurring it;</li> <li>replacing the invalid values in the original image with what I got from point 3.</li> <li>run a median filter of size 10.</li> </ol> <pre class="lang-default prettyprint-override"><code>img2 = img; img2(img &lt; .005) = mean(img(:)); H = fspecial('disk',10); img3 = imfilter(img2,H,'symmetric'); img4 = img; img4(img &lt; .3) = img3(img &lt; .3); filterSize = 10; padopt = {'zeros','indexed','symmetric'}; IMG = medfilt2(img4, [1 1]*filterSize, padopt{p}); </code></pre> <p><img src="https://i.stack.imgur.com/Zb1tm.png" alt="Second trial"></p>
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