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How to denoise images using wavelet packet transform(WPT) in Matlab #6980

Closed queenterbruce063 closed 2 years ago

queenterbruce063 commented 2 years ago

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How to denoise images using wavelet packet transform in Matlab

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https://www.section.io/engineering-education/implementation-of-convolution-integral-of-continuous-time-linear-time-invariant-systems-in-matlab/

How to denoise images using wavelet packet transform(WPT) in Matlab

Proposed article introduction

The wavelet packets are the generalized approach of wavelet decomposition which introduces a spacious area of the possibility of signal analysis that permits the better accordance analysis to the signal. It transforms the signal to the frequency domain level. WPT is a generalization of the orthogonal wavelet transform. Wavelet packets are used for finer analysis by breaking up high-frequency space into approximation and detailed space. In wavelet transform, these detailed spaces are not decomposed. Here, only the approximation space is split. This tutorial explains the basic theoretical background of WPT based denoising scheme, noise variance estimation and universal threshold calculation. The denoising is implemented in MATLAB to do experiments with different noisy 1D and 2D signals. The concept of full tree and best tree-based decomposition is also included.

Key takeaways

Article quality

In this article, we cover the WPT into details and how it can be applied in Matlab. This include the Matlab functions for this transform.

github-actions[bot] commented 2 years ago

👋 @queenterbruce063 Good afternoon and thank you for submitting your topic suggestion. Your topic form has been entered into our queue and should be reviewed (for approval) as soon as a content moderator is finished reviewing the ones in the queue before it.

ahmadmardeni1 commented 2 years ago

Thank you for submitting your topic. After some careful consideration, it struck us that this topic may be a bit over-saturated throughout other blog sites and official documentation.

We believe this is the best way for students to build a great portfolio (for potential employers) is by building what does not exist and what can provide the most value.

Please feel free to suggest an alternate topic to explore. 🚀