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Diff between discrete cosine and wavelet

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Dec 24, 2005
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signal denoising discrete cosine transform


Diff between discrete cosine and wavelet

wat makes the former more stronger..

appications where they are used specifically..


DCT is the type of Fourier transform, in this transform cosines are basis functions,where as in wavelet transform wavelet is the basis funtion.that means in DCT your signal is represented in terms of cos functions where as in wavelet transform signal is represented with shifted and scled version of mother wavelet.

Beauty of wavelet transform is time -frequency representation and basis choice.

Added after 2 minutes:

Sorry i forgot to mention about applications of DCT and wavelet transform(WT)
mostly DCT is used in Image compression, where as wavelet transform is also useful in image compression, Image denoising,signal denoising,Transient signal processing,time-freq representation.

A discrete cosine transform (DCT) is a Fourier-related transform similar to the discrete Fourier transform (DFT), but using only real numbers. DCTs are equivalent to DFTs of roughly twice the length

DCT is used in JPEG image compression, MJPEG, MPEG, and DV video compression

DCTs are also widely employed in solving partial differential equations by spectral methods

Wavlet is time-freq representation of signal.
Wavelets are used in numerous applications including
They can do multiresolution analysis of a signal which is not possible in DCT as it has only one resolution that of the frequency.
Feature Extraction
and other engg applications as well.
Numerous type of Wavelets are available includind Haar,Gabor,Mexican Hat you can even create your own wavelet functions



Now i am doing palm print recognition, may i ask Discrete Cosine and wavelet which is better?
How am i develop it in my project after i extract the palm line from the palm?

Thanks in advance.:cry:

Use wavelets. Wavelets is able to generate better image feature (I assume you will capture palm print using imaging system) compared to DCT. As given in the first two reply, wavelets has the ability to represent signal/image in time-freq localisation which Fourier basis are only well represented in freq domain. So, why you are needed good time-freq representation for your palm features? That is to ensure the captured palm feature has spatial geamentry invariant properties. Thus, the recognition performance will be improved.

Added after 2 minutes:

For the palm lines, you can refer to some papers on the topics of wavelet singularities detection. From there you should be able to construct a good wavelet represntation of your palm features. Search for Mallat's papers for the topics, he is the Guru of that.

Hello Yok,

Actually i already extracted the palm lines from the palm by using sobel operator...
But now i am in stuck....i don't know how to implement the wavelet in the palm print feature extraction for classification?
Hope you can guide me....

Thanks in advance.:|

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