Local Approximation Signal and Image Processing

1D Adaptive-Scale DemoBox

for MATLAB version 6.5 or later


The 1D Adaptive-Scale Selection DemoBox is a set of MATLAB routines for 1D signal denoising. They implement a recent new development in the area of statistical scale-adaptive local approximation techniques.

The main algorithms are prepared as demos, so that they can be executed in a straightforward manner. These demos reproduce figures and results from the publications by the authors of the LASIP project and their collaborators.

All the provided demos are open-source, and may be modified and tuned to be exploited with other data. This DemoBox is available free-of-charge for educational and non-profit scientific research, enabling others researchers to understand and reproduce our work. Any unauthorized use of the LASIP routines for industrial or profit-oriented activities is expressively prohibited.



The main routines provided in this DemoBox are the following:

demo_CreateLPAKernels.m

LPA kernel design
Calculates the LPA convolution smoothing and differentiation kernels of polynomial approximation and its frequency response characteristic, and draws them.
demo_LPAICI_1D.m

LPA-ICI denoising
Performs the Anisotropic LPA-ICI denoising on observations which are contaminated by additive white Gaussian noise.
demo_MedianICI_1D.m

Median-ICI denoising
Performs the Anisotropic Median-ICI denoising on observations which are contaminated by the additive white Gaussian and impulsive noise.
demo_IdealInvariantScale1D.m

Oracle Invariant scale selection
Illustrates the problem of invariant scale selection. The invariant ideal scale h of the LPA estimator is found for the noisy signal assuming that the true signal is known.
demo_IdealVaryinigScale1D.m

Oracle Varying scale selection
Illustrates optimal scale selection for every point of the signal. The varying ideal scale h of the LPA estimator is found for the noisy signal assuming that the true signal is known. Ideal scale is selected by minimization of mean square error in a point-wise manner.
Any unauthorized use of the LASIP routines for industrial or profit-oriented activities is expressively prohibited. By downloading any of the LASIP files, you implicitly agree to all the terms of the LASIP limited license PDF.


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Tampere University of Technology - Department of Signal Processing - Transforms and Spectral Methods Group