wavelet

I am currently diving into Wavelets and are a bit confused about certain things. First of all, this is NOT homework. Its for recreational coding only. In order to gain a better understanding, I implemented the lifting-scheme for the LeGal 5/3 wavelet in C. As far as I can see, it seems to work. I can reverse it and the original images is reproduced correctly. In pseudo-code, my forward dwt looks like this: // deinterleave splits the low band from the high band // (e.g. 1 0 3 0 6 0 8 1 11 becomes 1 3 6 8 11 | 0 0 0 1) for each row in image: dwt1d(row) deinterleave(row) for each col in image:

I am trying to use the functions provided in the Matlab Wavelet Toolbox to create a multi-level discrete wavelet decomposition of an image, extracting the coefficients, manipulating them, and recomposing them back into the image. I tried using a number of functions but none of them seem to do what I need. These are the steps to do this. Use wavedec2 to decompose the image into [C,S]. [C,S] = wavedec2(X,N,Lo_D,Hi_D) I then must use detcoef2 to extract the detail coefficients from [C,S]. [C,S] is the 'wavelet decomposition structure', it does not represent the actual coefficients such as cD, cH,

I am using MATLAB to apply the Discrete Wavelet Transform on an image. I am applying it several times (3) in order to get a 3 level transform. I am using the dwt2 function provided by MATLAB in order to compress and idwt2 to make the decompression. The problem is that I do not know how to decompress several times, as in apply idwt2 several times to the previous received output, as it returns a matrix. Take for example: x = idwt2(scaled3, vertical3, horizontal3, diagonal3, Lo_R, Ho_R); How should idwt2 be applied to x? Looking at the documentation for dwt2 and idwt2 , it appears that you have 2

I am searching for alternatives to the FFT to create a spectrogram analyser in python. I heard that the wavelet transform is faster and provides better time accuracy than the short time FFT. I went in this wikipedia article that features the Haar wavelet transform implementation in Java: https://en.wikipedia.org/wiki/Discrete_wavelet_transform#Code_example I brutally converted it to python but I have no idea if the values I'm getting are correct. Can someone confirm? from math import * N = 8 res = [sin(k) for k in xrange(N)] for k in xrange(N): print res[k] print def