Image processing based on wavelet transform in python [closed]

1. How wavelet transform is used in image processing?
2. What is the disadvantage of wavelet transform?
3. Why discrete wavelet transform is used in image processing?

How wavelet transform is used in image processing?

Using wavelet transform, image can be decomposed at different levels of resolution as wavelet decomposition has varying window size and can also be processed from low resolution to high resolution as wavelet transformation is localized both in time and frequency domains.

What is the disadvantage of wavelet transform?

Although the discrete wavelet transform (DWT) is a powerful tool for signal and image processing, it has three serious disadvantages: shift sensitivity, poor directionality, and lack of phase information.

Why discrete wavelet transform is used in image processing?

The DWT decomposes a digital signal into different subbands so that the lower frequency subbands have finer frequency resolution and coarser time resolution compared to the higher frequency subbands. DWT is the basis of the new JPEG2000 image compression standard.