tuxiangfenge.rar_遗传算法

O=imread('Lenna.bmp'); figure(1);imshow(O); NIND = 40; % Number of individuals MAXGEN =50; % Maximum no. of generations PRECI = 8; % Precision of variables GGAP = 0.9; % Generation gap % Build field descriptor FieldD = [8;1;256;1;0;1;1]; % Initialise population Chrom = crtbp(NIND, PRECI); gen = 0;% Counter phen=bs2rv(Chrom,FieldD);% Evaluate initial population ObjV = target(O,phen); while gen < MAXGEN,% Generational loop % Assign fitness values to entire population FitnV = ranking(-ObjV); SelCh = select('sus', Chrom, FitnV, GGAP);% Select individuals for breeding SelCh = recombin('xovsp',SelCh,0.7);% Recombine individuals (crossover) SelCh = mut(SelCh);% Apply mutation phenSel = bs2rv(SelCh,FieldD);% Evaluate offspring, call objective function ObjVSel=target(O,phenSel); [Chrom ObjV]=reins(Chrom,SelCh,1,1,ObjV,ObjVSel);% Reinsert offspring into population gen = gen+1;% Increment counter end [Y,I]=max(ObjV); M=bs2rv(Chrom(I,:),FieldD) [m,n]=size(O); for i=1:m for j=1:n if O(i,j)>M O(i,j)=256; end end end figure(2) imshow(O);