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  2. Sub-band coding - Wikipedia

    en.wikipedia.org/wiki/Sub-band_coding

    Subband coding resides at the heart of the popular MP3 format (more properly known as MPEG-1 Audio Layer III), for example. Sub-band coding is used in the G.722 codec which uses sub-band adaptive differential pulse code modulation (SB-ADPCM) within a bit rate of 64 kbit/s. In the SB-ADPCM technique, the frequency band is split into two sub ...

  3. Embedded zerotrees of wavelet transforms - Wikipedia

    en.wikipedia.org/wiki/Embedded_Zerotrees_of...

    Embedded zerotree wavelet algorithm (EZW) as developed by J. Shapiro in 1993, enables scalable image transmission and decoding. It is based on four key concepts: first, it should be a discrete wavelet transform or hierarchical subband decomposition; second, it should predict the absence of significant information when exploring the self-similarity inherent in images; third, it has entropy ...

  4. Martin Vetterli - Wikipedia

    en.wikipedia.org/wiki/Martin_Vetterli

    Martin Vetterli is a co-author of the book Wavelets and Subband Coding (Prentice-Hall, 1995). [9] In 2008, Vetterli authored with Paolo Prandoni a free textbook Signal Processing for Communications. [10]

  5. Wavelet packet decomposition - Wikipedia

    en.wikipedia.org/wiki/Wavelet_packet_decomposition

    Originally known as optimal subband tree structuring (SB-TS), also called wavelet packet decomposition (WPD; sometimes known as just wavelet packets or subband tree), is a wavelet transform where the discrete-time (sampled) signal is passed through more filters than the discrete wavelet transform (DWT).

  6. Discrete wavelet transform - Wikipedia

    en.wikipedia.org/wiki/Discrete_wavelet_transform

    There are far fewer significant components in the wavelet domain in this example than there are in the time domain, and most of the significant components are towards the coarser coefficients on the left. Hence, natural signals are compressible in the wavelet domain. The wavelet transform is a multiresolution, bandpass representation of a signal.

  7. The wavelets generated by the separable DWT procedure are highly shift variant. A small shift in the input signal changes the wavelet coefficients to a large extent. Also, these wavelets are almost equal in their magnitude in all directions and thus do not reflect the orientation or directivity that could be present in the multidimensional signal.

  8. Wavelet - Wikipedia

    en.wikipedia.org/wiki/Wavelet

    The wavelets are scaled and translated copies (known as "daughter wavelets") of a finite-length or fast-decaying oscillating waveform (known as the "mother wavelet"). Wavelet transforms have advantages over traditional Fourier transforms for representing functions that have discontinuities and sharp peaks, and for accurately deconstructing and ...

  9. Fast wavelet transform - Wikipedia

    en.wikipedia.org/wiki/Fast_wavelet_transform

    The fast wavelet transform is a mathematical algorithm designed to turn a waveform or signal in the time domain into a sequence of coefficients based on an orthogonal basis of small finite waves, or wavelets. The transform can be easily extended to multidimensional signals, such as images, where the time domain is replaced with the space domain.