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I have images where there is a lot of "black" background (few shades of black). (In many images at least half the pixels are background). I need to get interest points from the image, but because the background is not smooth (although black) , I get a lot of "false" key points in the background. What filter/s will fit best to keep the details in the image but will smooth the background as much as possible ? I tried median filter, but the size needed to reduce background noise ([5 5]) was to strong for the small details in the image I wanted to keep sharp, same for Gaussian with very small sigma.

Thanks

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Can you add some images here? –  Mohammad Feb 18 '13 at 5:58
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For small noises erosion followed by dilation can help as the erosion will clear the noise and dilation will bring back the deleted boundaries.Though i have still not implemented this Erosion+dilation option myself on grayscale but may be they can help

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You can reduce image size or use scale-invariant interest point detector which can deal with blurry images.

Please note that using some elaborate denoising algorithm may change each image in a slightly different way, thus possibly distorting the positions of your interest points.

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