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Lagrange wavelets for signal processing
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DOI：10.1109/83.951535.png)
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Abstract
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This paper deals with the design of interpolating wavelets based on a variety of Lagrange functions, combined with novel signal processing techniques for digital imaging. Halfband Lagrange wavelets, B-spline Lagrange wavelets and Gaussian Lagrange [Lagrange distributed approximating functional (DAF)] wavelets are presented as specific examples of the generalized Lagrange wavelets. Our approach combines the perceptually dependent visual group normalization (VGN) technique and a softer logic masking (SLM) method. These are utilized to rescale the wavelet coefficients, remove perceptual redundancy and obtain good visual performance for digital image processing.
Keywords:
distributed approximating functionals
generalized Lagrange wavelets
softer logic masking
visual group normalization
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