Noises present in communication channels are disturbing and
the recovery of the original signals from the path without any noise is very
difficult task. This is achieved by denoising techniques that remove noises
from a digital signal. Many denoising technique have been proposed for the removal
of noises from the digital audio signals. But the effectiveness of those
techniques is less. In this Post, an audio denoising technique based on wavelet
transformation is implemented.
Denoising is performed in the transformation
domain and the improvement in denoising is achieved by a process of grouping
closer blocks. The technique exposes each and every finest details contributed
by the set of blocks and also it protects the vital features of every
individual block. The blocks are filtered and replaced in their original
positions. The grouped blocks overlap each other and thus for every element a
much different estimation is obtained. A technique based on this denoising
strategy and its efficient implementation is presented in full detail. The implementation
results reveal that the proposed technique achieves a state-of-the-art
denoising performance in terms of both signal-to-noise ratio and audible quality.
MATLAB Implementation of code:
Fig: Using Hard Threshold
Fig: Using Soft Threshold
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