matlab使用神经网络实现图像压缩

clc;

clear all;

I=imread('lv.jpg');

I=rgb2gray(I);

I=imresize(I,[128,128]);

figure;

imshow(I);

p=[];

for i=1:32   %预处理取4*4的字块，最后生成16*1024的矩阵

    for j=1:32

        I2=I((i-1)*4+1:i*4,(j-1)*4+1:j*4);

        i3=reshape(I2,16,1);

        II=double(i3);

        p_1=II/255;

        p=[p,p_1];

    end

end

t=p;

net=newff(minmax(p),[2,16],{'tansig','logsig'},'trainlm');  %构建网络第一层8第二层16

net.trainParam.goal=0.001;   %均方差为0.001；输出和目标值的差的平方再求平均值

net.trainParam.epochs=500;    %训练次数为500次，什么迭代次数

tic    %开始计时

net=train(net,p,t);   %用该网络进行训练

toc    %结束计时，在最后的时候回输出运行的时间

Y_chonggou=sim(net,p);   %仿真相当于windows中的run命令,运行net网络

Ychonggou_ceshi=[];

for k=1:1024

    Ychonggou_ceshi1=reshape(Y_chonggou(:,k),4,4);

    Ychonggou_ceshi=[Ychonggou_ceshi,Ychonggou_ceshi1];

end

YYchonggou_ceshi=[];

for k=1:32

    YYchonggou_ceshi1=Ychonggou_ceshi(:,(k-1)*128+1:k*128);

    YYchonggou_ceshi=[YYchonggou_ceshi;YYchonggou_ceshi1];

end

Ychonggou_ce=uint8(YYchonggou_ceshi*255);

figure;

imshow(Ychonggou_ce);