Audio Compression Using Wavelet Transform with Parameter Comparison
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Resource Overview
Detailed Documentation
The primary objective of this program is to achieve audio compression using wavelet transform functions. The implementation involves applying discrete wavelet transform (DWT) to decompose audio signals into approximation and detail coefficients, followed by threshold-based coefficient quantization for compression. During the compression process, users can experiment with various wavelet families (such as Daubechies, Haar, or Symlets) and multiple compression iterations to observe differences in the reconstructed audio files. The algorithm typically includes steps for signal decomposition, coefficient thresholding, quantization, and reconstruction using inverse DWT. This approach allows for exploration of different compression strategies and optimization methods, including adjustable threshold parameters and wavelet selection, to achieve improved audio compression results while maintaining perceptual quality.
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