 # MATLAB代做-python代做-PCNN算法的图像分割

### 时间：2018-12-30 0:50:29 点击： 核心提示：MATLAB代做-python代做-PCNN算法的图像分割...
clear all
figure(1);
imshow(RGB);
imwrite(RGB,'分割结果\park.jpg','jpg');
HSV = rgb2hsv(RGB); % Transform from RGB to HSV
H = HSV(:,:,1);
S = HSV(:,:,2);
V = HSV(:,:,3);
H = H+0.22;
INDEX = find(H>1);
H(INDEX) = H(INDEX) - 1;
figure(24);
imshow(H);
imwrite(H,'分割结果\park_H_revolve.jpg','jpg');
% Color quantization
QH = 16;
QS = 4;
QV = 4;
scopeH = 1 / QH;
scopeS = 1 / QS;
scopeV = 1 / QV;

siz = size(H);
M = siz(1) * siz(2);
temp = zeros(siz);
HHH = temp;
SSS = temp;
VVV = temp;
% Quantize H
for i = 1:QH
k = find((H < i*scopeH) & (H >= (i-1)*scopeH));
HHH(k) = i;
end
% Quantize S
for i = 1:QS
k = find((S < i*scopeS) & (S >= (i-1)*scopeS));
SSS(k) = i;
end
% Quantize V
for i = 1:QV
k = find((V < i*scopeV) & (V >= (i-1)*scopeV));
VVV(k) = i
end

% Color label
QI = temp;         % label matrix, used to statistic Ck
for i = 1:siz(1)
for j = 1:siz(2)
QI(i,j) = (HHH(i,j) -1)*QS*QV + (SSS(i,j) - 1)*QV + VVV(i,j);
end
end

eQI = uint8(QI);
figure(35);
imshow(eQI);
imwrite(eQI,'分割结果\park_quantitation.jpg','jpg');
%imwrite(eQI,['Lajiao_VQofHSV','.bmp'],'bmp');

%figure(112);
%EDG2 = edge(eQI,'canny');
%imshow(EDG2);
%imwrite(EDG2,['Lajiao_VQofHSV_edg','.bmp'],'bmp');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Double PCNN
[row, col] = size(QI);
Va = max(max(QI));
Vb = min(min(QI));

F = QI;

vl = 1;
vt = 500;

l_deta = 1;
l_t = 0.5;

beta = 0.012;

t_deta = 1;
t_t = 25;
threshold = t_deta*1 / t_t;

%step = 20;%optimize
step = 20;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
TEMP=zeros(row,col);
%%%%%%%%%%% to create W %%%%%%%%%%%%%%
%Ws=[0 1 0;1 1 1;0 1 0];
%%%%%%%%%%%%%%%%%%%%%
deta = 2;
if i==halfR & j==halfR
K_r(halfR, halfR)=1;
K_r2(halfR, halfR)=1;
else
K_r(i,j) = 1/sqrt((i-halfR)^2 + (j-halfR)^2);
end
end
end
Ws = K_r;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%% start program %%%%%%%%%%%%%
%%%% factor loop %%%%%
Y_threshold = TEMP;
Y_time = TEMP;
Y1 = TEMP;
Y2 = TEMP;
Y = TEMP;
Ya = TEMP;
Yb = TEMP;
Edge_image=TEMP;
L = TEMP;
U = TEMP;
T1 = TEMP + Va;
T2 = TEMP + Vb;
j = 1;

%%% determine when exit loop
accuYTrue = 1;
iterTrue = 1;
accY = TEMP;  % Accumulate total neuros of firing

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
while iterTrue
j
invar_fig=1;change_mark=0;k=0;
%%%%%%%%%%%%%%%
while (invar_fig==1)
m
mid_Y=Y;
U=internal24(F,L,Y,beta);
Y1 = pulse1(U, T1);
%Y2 = pulse2(U, T2);
Y = Y1; % + Y2;
%Y=pulse_p(U,T,L);
if (mid_Y==Y)
invar_fig=0;
elseif m>30 & change_mark==0
mid_Y1=mid_Y;
mid_Y2=Y;
change_mark=1;
elseif change_mark==1 & k<1
k=1;
elseif k==1
%if mid_Y1==mid_Y & mid_Y2==Y
invar_fig=0;
%else
% change_mark=0;k=0;
% end
end
m=m+1;
end
%%%%save threshold for fired pixels (sigle-pass)%%%%%%
%%%%%%%statistc numbers of nurons in plusing areas %%%%%%
index1 = find(Y1 ~= 0);%find index of element of noequal zero(index of pulsing neurons)
q = size(index1, 1);
if q ~= 0     %%% statistic pulsing neurons %%%
for yy = 1:row
for zz = 1:col
if(Y1(yy, zz) == 1)
Y_threshold(yy, zz) = round(T1(yy, zz));
Y_time(yy, zz) = j;
end
end
end   %%% statistic end %%%
end

Ya = Ya + Y1;
T1 = threshold1(T1, Ya, Va, step);  %decrement threshold(linear decay)%%%%%%%%%%
j=j+1;
%%%%%%%%%%%%%%%%%%%%%
accY = accY + Y;
index = find(accY == 0);
size(index);
if ans(1) == 0
iterTrue = 0;
end                       % Exit loop
end

figure(59);
Y_pcnn = uint8(Y_threshold)
imshow(Y_pcnn);
imwrite(Y_pcnn,'分割结果\park_pcnn_segm2.bmp','bmp');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

QQ ：1224848052 Tags:PCNN算法

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