Removing outliers from a grey-scale image

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).

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.

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P.S. Someone has already suggested me to use a fast wavelet reconstruction, but I would not really know where to start...

Answer 1

[Image Analyst]

It looks like all your outlier data is dark. So I'd just threshold it and then use roifill() to smear the surrounding area into the black areas.

binaryImage = grayImage < 50; % or whatever.
binaryImage = imdilate(binaryImage, true(5)); % Enlarge it somewhat.
fixedImage = roifill(grayImage, binaryImage);

Try that. You might have to play around with the dilation amount and the threshold value.