Mercurial > hg > smallbox
view Problems/private/genPDF.m @ 50:d5155eaa3f68
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author | idamnjanovic |
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date | Mon, 14 Mar 2011 16:51:46 +0000 |
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function [pdf,val] = genPDF(imSize,p,pctg,distType,radius,disp) %[pdf,val] = genPDF(imSize,p,pctg [,distType,radius,disp]) % % generates a pdf for a 1d or 2d random sampling pattern % with polynomial variable density sampling % % Input: % imSize - size of matrix or vector % p - power of polynomial % pctg - partial sampling factor e.g. 0.5 for half % distType - 1 or 2 for L1 or L2 distance measure % radius - radius of fully sampled center % disp - display output % % Output: % pdf - the pdf % val - min sampling density % % % Example: % [pdf,val] = genPDF([128,128],2,0.5,2,0,1); % % (c) Michael Lustig 2007 % This file is used with the kind permission of Michael Lustig % (mlustig@stanford.edu), and originally appeared in the % SparseMRI toolbox, http://www.stanford.edu/~mlustig/ . % % $Id: genPDF.m 1040 2008-06-26 20:29:02Z ewout78 $ if nargin < 4 distType = 2; end if nargin < 5 radius = 0; end if nargin < 6 disp = 0; end minval=0; maxval=1; val = 0.5; if length(imSize)==1 imSize = [imSize,1]; end sx = imSize(1); sy = imSize(2); PCTG = floor(pctg*sx*sy); if sum(imSize==1)==0 % 2D [x,y] = meshgrid(linspace(-1,1,sy),linspace(-1,1,sx)); switch distType case 1 r = max(abs(x),abs(y)); otherwise r = sqrt(x.^2+y.^2); r = r/max(abs(r(:))); end else %1d r = abs(linspace(-1,1,max(sx,sy))); end idx = find(r<radius); pdf = (1-r).^p; pdf(idx) = 1; if floor(sum(pdf(:))) > PCTG error('infeasible without undersampling dc, increase p'); end % begin bisection while(1) val = minval/2 + maxval/2; pdf = (1-r).^p + val; pdf(find(pdf>1)) = 1; pdf(idx)=1; N = floor(sum(pdf(:))); if N > PCTG % infeasible maxval=val; end if N < PCTG % feasible, but not optimal minval=val; end if N==PCTG % optimal break; end end if disp figure, subplot(211), imshow(pdf) if sum(imSize==1)==0 subplot(212), plot(pdf(end/2+1,:)); else subplot(212), plot(pdf); end end