estbeta.m

基于小波变换的特征检索算法

function beta = estbeta(m1, m2)
% ESTBETA Estimate the beta parameter of a generalized Gaussian 
%
% Input:
%	m1: average absolute values of subband coefficients
%	m2: variances of subband coefficients
%
% Output:
%	beta: paramaters of generalized Gaussian p.d.f.
%	f(x) = K * exp(-(abs(x) / alpha)^beta)
%
% See also: ESPPDF, SBPDF
%
% Note:	This is a faster version that computes beta using interpolation
%	where SBPDF use FZERO to solve inverse function

% beta = F^(-1)(m1^2 / m2);

x = 0.05 * [1:100]';
f = [2.4663e-05 0.004612 0.026349 0.062937 0.10606 0.15013 0.19234 0.23155 ...
     0.26742 0.3 0.32951 0.35624 0.38047 0.40247 0.42251 0.44079 0.45753 ...
     0.47287 0.48699 0.5 0.51202 0.52316 0.53349 0.5431 0.55206 0.56042 ...
     0.56823 0.57556 0.58243 0.58888 0.59495 0.60068 0.60607 0.61118 ...
     0.616 0.62057 0.6249 0.62901 0.63291 0.63662 0.64015 0.64352 ...
     0.64672 0.64978 0.65271 0.6555 0.65817 0.66073 0.66317 0.66552 ...
     0.66777 0.66993 0.672 0.674 0.67591 0.67775 0.67953 0.68123 0.68288 ...
     0.68446 0.68599 0.68747 0.68889 0.69026 0.69159 0.69287 0.69412 ...
     0.69532 0.69648 0.6976 0.69869 0.69974 0.70076 0.70175 0.70271 ...
     0.70365 0.70455 0.70543 0.70628 0.70711 0.70791 0.70869 0.70945 ...
     0.71019 0.71091 0.71161 0.71229 0.71295 0.71359 0.71422 0.71483 ...
     0.71543 0.71601 0.71657 0.71712 0.71766 0.71819 0.7187 0.7192 0.71968];

val = m1^2 / m2;
if val < f(1)
    beta = 0.05;
elseif val > f(end)
    beta = 5;
else
    beta = interp1q(f, x, val);%原函数是f(x),在非转折点插入点，得f在val上的函数值beta，beta与val有相同的大小
end