I'm reading a paper where image classification is done. Their approach is to use the discrete wavelet transform with bi-orthogonal wavelets of degree 3.5 and decomposition of level 3 on images. Based on the 2d coefficients gotten from the DWT they calculate statistical features such as standard deviation, skew, kurtosis, mean, absolute deviation. These statistical features are used as input for classification.
My question is now, are these statistical features based on the DWT rotation/scale/translation invariant ? I personally do not think so. But I can't motivate my answer. Can someone explain this, I'd appreciate if you can quote a source if you anwer.