Good question my friend, however, we may have to specify which type of WT we need to investigate... the continuous wavelet transform and wavelet coherence is widely used in biomedical applications or in any application that require scrutinising a non stationary signal in the time-frequency domain ... finding high power region....and it does not require an inverse transform. Whereas the DWT is useful in different applications that require signal enhancement by analysing the signal, do some processing such as denoising etc, then an inverse DWT for perfect signal reconstruction.

The Discrete Wavelet Transform (DWT) approximation coefficient is a low-resolution version of the original image. Apart from noise reduction to some extent it will not provide any extra feature for classification. The detail coefficients on the other hand will provide information regarding texture orientations along specific directions, which can be used for classification, if certain classes are characterized by strong textures along specific directions.

Thank you Yahya T Qassim

Thank you Ranjan Parekh

Thank you Andrzej Katunin

Thank you so much dear Muhammad Tariq Sadiq

Many thanks dera Ateeq Ur Rehman

Thanks to share this question but I am chemist

ok Rasha Shaker Nima , thank you

Thanks for sharing

ok dear Suhad Mohammed , thank you

Interesting question but it is away from my field

Many thanks dear Lamia Mustafa Al-Naama for your support

Anyone here interested in Wavelets?

Follow my dissertation about PCBs Fast Wavelet Transform.

Please, download and read it!

Link:

http://repositorio.unicamp.br/jspui/bitstream/REPOSIP/338849/1/Bonello_DanielKatz_M.pdf

Iam interesting.

MANY THANKS DEAR Karrar S. Faraj

🌹🌹 Dear

Firas Mahmood Mustafa