frit_nla.m

脊波工具和相关实验以及有关实验数据

function imrec = frit_nla(im, wname, ncoefs, plotflag)
% FRIT_NLA  FRIT non-linear approximation
%
%	imrec = frit_nla(im, wname, ncoefs, [plotflag])
%
% Input
%	im:	Input image
%	wname:	wavelet name used in the FRIT
%	ncoefs:	vector contains the numbers of most significant coefs
%
% Output
%	imrec:	cell vector contain the images reconstructed by NLA

% maximum radius of directions that used by wavelet in the FRIT
maxR = 3;

% Take the FRIT
[r, s, m] = fritm(im, wname, maxR);
% [r, s, m] = frito(im, wname);

% Sort 
rsort = sort(abs(r(:)));
rsort = flipud(rsort);

lk = length(ncoefs);
imrec = cell(1, lk);

% Non-linear or N-best terms approximation
for k = 1:lk
    rn = r .* (abs(r) > rsort(ncoefs(k)));    
    
    imrec{k} = ifritm(rn, s, m, wname, maxR);
    % imrec = ifrito(rn, s, m, wname); 
end

if exist('plotflag', 'var')    
    clf;
    
    % range = [-.25, 1.25];
    range = [0, 1];

    colormap('gray');
    
    for k = 1:lk
	% subplot(floor(sqrt(lk)), floor(sqrt(lk)), k);
	subplot(1, lk, k);
	imagesc(imrec{k}, range);
	axis image, 
	axis off,
	title(sprintf('%d coefficients\n(SNR = %0.2f dB)', ...
		      ncoefs(k), SNR(im, imrec{k})), 'FontSize', 9);
	
    % title(sprintf('First %d coefficients', ncoefs(k)), 'FontSize', 10);
    end
end