Daubechies wavelet
A family of orthogonal, compactly supported real wavelets introduced by Ingrid Daubechies. They have the maximum number of vanishing moments and are widely used in signal processing and image compression.
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The Haar wavelet has weak frequency-domain localization ability, and its sparse representation of smooth signals is inferior to that of more complex wavelets such as Daubechies.
Real wavelets (such as Haar, Daubechies, Symlet) are computationally efficient, have real coefficients, have low storage and transmission costs, are good at detecting abrupt points and discontinuities in signals, and are widely used in image compression (such as JPEG 2000) and singularity detection.
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The Haar wavelet has weak frequency-domain localization ability, and its sparse representation of smooth signals is inferior to that of more complex wavelets such as Daubechies.
50%UnverifiedReal wavelets (such as Haar, Daubechies, Symlet) are computationally efficient, have real coefficients, have low storage and transmission costs, are good at detecting abrupt points and discontinuities in signals, and are widely used in image compression (such as JPEG 2000) and singularity detection.
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