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  • Hey all, just changed over the backend after 15 years I figured time to give it a bit of an update, its probably gonna be a bit weird for most of you and i am sure there is a few bugs to work out but it should kinda work the same as before... hopefully :)

What transform CODEC is better? (WCT) or (DCT)? A challenge to explore deep into!

Neil Abeynayake

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I don't care what Jim or Jarred sprouts out, I see image deficiencies between the two. I wouldn't blame you for for NOT noticing anomalies between the two due to your age or poor eyesight variances, etc. Please be objective and professional about what we are discussing about.



Here is a one of the transcripts from a user that posted on a prominent website:



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https://dsp.stackexchange.com/questions/24793/why-wavelet-based-transform-is-more-suitable-for-image-compression-compared-to-d


Both JPEG and JPEG 2000 use the change of basis compression type.

Namely, we transform the data into a different representation assuming in this representation the number of parameters needed to describe to data is lower.
Or to the least, most of the information is gathered within few parameters.

Now, if you look at the energy level of the DCT coefficients of real world images you'd see most of the energy is limited to the very few coefficients.
This is what JPG does, keeps only the few dominant coefficients and throws the rest.

How efficient is DCT?
It depends on how less coefficients are needed to describe the image in an acceptable quality.

It turns out that for Wavelets the situation is better.
Namely on real world images less coefficients are needed to describe the image with the same perceived quality.

This property is called the ability to decorrelate the data / being energy densed, etc...

At the end, it is all up to how much less parameters are needed to describe the same data.

P.S.
Using SVD / KLT (They are equivalent in this sense) would be even more efficient in the sense of how much less coefficients are needed for the same quality (In the [FONT=MathJax_Main]ℓ[/FONT][FONT=MathJax_Main]2[/FONT]

sense).
The problem is those bases are adaptive to the data and hence if you use them you have to include them to be able to decompress the data.
What's so nice, you can ask which, in general, approximate the SVD better?
It turns out that Wavelets are better doing so.


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