iwt_ai.sci

小波分解源代码

function beta = IWT_AI(wc,L,D,F,EF)
// IWT_AI -- Inverse transform, average-interpolating wavelets
//  Usage
//    x = IWT_AI(wc,L,D)
//  Inputs
//    wc    1-d wavelet transform; length(x) = 2^J
//    L     coarsest resolution. L << J
//    D     degree of polynomials for average interpolation
//  Outputs
//    x     1-d signal reconstructed from wc
//
//  Description
//    IWT_AI implements a 1-d inverse wavelet transform of data which
//    arise as the outputs of boxcar integrators.  The ideas are
//    described in ``Smooth Wavelet Decompositions with Blocky
//    Coefficient Kernels.''  See BlockyDemo and the directory
//    Scripts/Blocky.
//For Example:
//   wc=1:1024;
//   L=8;
//   D=10;
//   beta=IWT_AI(wc,L,D);
//  See Also
//    FWT_AI, FWT_DD, FWT_PO 
//
//  Copyright Aldo I Maalouf

    [lhs,rhs]=argn()
        
        if rhs == 3,
	  F = MakeAIFilter(D);
	  EF = MakeAIBdryFilter(D);
	end
	
	[n,J] = dyadlength(wc);
	w     = ShapeAsRow(wc);
	beta  = w(1:(2^L));
//
	for j=L:(J-1) ,
	   beta = AIDyadUp(beta,w(dyad(j)),D,F,EF);
	end
//
	x = ShapeLike(beta,wc);
endfunction