python,haar-wavelet,wavelet-transform

Your request is clear. Have you tried Pyscellania's normalised or standard Haar Wavelet? Maybe you are just using the wrong one. ...

opencv,image-processing,image-segmentation,wavelet,wavelet-transform

Instead of attempting to use the traditional wavelet transform, you may want to try Haar-like wavelets tuned for object detection tasks, similar to the basis of integral images used in the Viola Jones face detector. This paper by Lienhart et al, used for generic object detection, would be a good...

signal-processing,fft,wavelet,haar-wavelet,wavelet-transform

note that, the width of the winow function is constant throughout the entire STFT process. and the time (t) in the function g(t-t') indicate sthat, t: is the current time on the time axis and it is variable each time the window is moved/shifted to the righ to overlap the...

python,scipy,wavelet-transform

I had the same question myself. Looking at the source code, my best guest is that the units are in "number of samples". The key code line within scipy.signal.wavelets.cwt is: wavelet_data = wavelet(min(10 * width, len(data)), width) Here, "wavelet" is a function (builder of the mother wavelet) which receives parameters...

signal-processing,wavelet,haar-wavelet,wavelet-transform

the raw signal what ever it is measuring it is a function of time "time-domain" which means if we plotted the "time-domain" we will get one axes for the time (t), which is independent, and another axes for the Amplitude (x(t)) which is dependent variable on the time. Note that:...

matlab,signal-processing,wavelet,wavelet-transform,continuous-fourier

Because we are dealing with digitized signals. You can not plot an infinite amount of samples of your signal. That is why you need to specify some parameters prior to working with digitized signals, such as the sampling frequency. The sampling frequency gives you a relationship between your samples indices...

python,numpy,scipy,wavelet-transform

the third argument of scipy.signal.cwt is widths, which must larger than 1, so change your code to: scipy.signal.cwt(np.array(c), scipy.signal.morlet, np.arange(.01,.1,.01) * len(c)) ...