Can wavelets be used for complex texture discrimination? I've recently been studying wavelet analysis with a view to differentiating certain areas of texture images where the texture differs from the background pattern (which is quite random); for example a small ink smudge on a photo of sand or similar.

I've seen a lot of applications of Gabor wavelets used to pick out textural differences in things like fabrics, and other regular type patterns but I've not been able to find any applications of things like Daubechie/Harr wavelets for anything other than image compression.

Can different wavelet families be used to pick out textural differences such as my example or am I wasting my time?
I think you should just dig deeper and get your hands dirty. I have used Mathematica as it is the fastest way I can model something like this

As an example:

 

(* img *)

dwd = DiscreteWaveletTransform[img, BiorthogonalSplineWavelet[1, 3], 4]


Here's how the decomposition tree looks like



You can then extract every coefficient

coeffs = dwd[{___, 0 | 1 | 2 | 3}, {"Image", "ImageFunction" -&gt; Identity, ImageSize -&gt; 120}]


From left to right {0}, {1}, {2} and {3}.



And you can compare those to the coefficients after applying the 1 + Log[coeff^2] function to them