Huffman编码(哈夫曼编码)的Matlab实现.doc

clear allfprintf(Reading data.)data=imread(cameraman.tif);data=uint8(data);%读入数据，并将数据限制为uint8fprintf(Done!n)%编码压缩fprintf(compressing data.);zipped,info=norm2huff(data);fprintf(Done!n)%解压缩fprintf(compressing data.);unzipped=huff2norm(zipped,info);fprintf(Done!n)%测试是否无失真isOK=isequal(data(:),unzipped(:)%显示压缩效果whos data zipped unzipped function zipped,info=norm2huff(vector)ifisa(vector,uint8), error(input argument must be a uint8 vector)endvector=vector(:);%将输入向量转换为行向量f=frequency(vector);%计算个元素出现的概率simbols=find(f=0);f=f(simbols);%将元素按出现的概率排列f,sortindex=sot(f);simbols=simbols(sortindex);%产生码字 generate the codeword as the 52 bits of a doublelen=length(simbols);simbols_index=num2cell(1:len);codeword_tmp=cell(len,1);while length(f)1, index1=simbols_index1; index2=simbols_index2; codeword_tmp(index1)=addnode(codeword_tmp(index1),uint8(0); codeword_tmp(index2)=addnode(codeword_tmp(index2),uint8(1); f=sum(f(1:2) f(3:end); simbols_index=index1 index2 simbols_index(3:end); %将数据重新排列，是两个节点的频率尽量与前一个节点的频率想当 resort data in order to have two nodes with lower frequency as first to f,sortindex=sort(f); simbols_index=simbols_index(sortindex);end%对应相应的元素与码字codeword=cell(256:1);codeword(simbols)=codeword_tmp;%计算总的字符串长度len=0;for index=1:length(vector), len=len+length(codeworddouble(vector(index)+1);end%产生01序列string=repmat(uint8(0),1,len);pointer=1;for index=1:length(vector), code=codeworddouble(vector(index)+1; len=length(code); string(pointer+(0:len-1)=code; pointer=pointer+len;end%如果需要，加零len=length(string);pad=8-mod(len,8);if pad0, string=string uint8(zeros(1,pad);end%保存实际有用的码字codeword=codeword(simbols);codelen=zeros(size(codeword);weights=2.(0:23);maxcodelen=0;for index 1:length(codeword), len=length(codewordindex); if lenmaxcodelen, maxcodelen=len; end if len0, code=sum(weights(codewordindex=1); code=bitset(code,len+1); codewordindex=code; codelen(index)=len; endendcodeword=codeword:%计算压缩后的向量cols=length(string)/8;string=reshape(string,8,cols);weights=2.(0:7);zipped=uint8(weights*double(string);%存储一个稀疏矩阵huffcodes=sparse(1,1);% init sparse matrixfor index=1:numel(codeword), huffcodes(codeword(index),1)=simbols(index);end%产生信息结构体info.pad=pad;info.ratio=cols./length(vector);info.length=length(vector);info.maxcodelen=maxcodelen; function codeword_new=addnode(codeword_old,item)codeword_new=cell(size(codeword_old);for index=1:length(codeword_old), codeword_newindex=item codeword_oldindex;end function vector=huff2norm(zipped,info)%HUFF2NORM Huffman 解码器%HUFF2NORM(X,INFO)根据信息体结构 info 返回向量 zipped 的解码结果%矩阵参数以X(:)形式输入ifisa(zipped,uint8), error(input argument must be a uint8 vector)end%产生01序列len=length(zipped);string=repmat(uint8(0),1,len.*8);bitindex=1:8;for index+1:len, string(bitindex+8.*(index-1)=uint8(bitget(zipped(index),bitindex);end%调整字符串string=logical(string(:);% remove 0 paddinglen=length(string);%解码weights=2.(0:51);vector=repmat(uint8(0),1,info,length);vectorindex=1;codeindex=1;code=0;for index=1:len, code=bitset(code,codeindex,string(index); codeindex=codeindex+1; byte=decode(bitset(code,codeindex),info); if byte0,% vector(vectorindex)=byte-1; codeindex=1; code=0; vectorindex=vectorindex+1; endend function byte=decode(code,info)byte=info.huffcodes(code); function f=frequency(vector)%FREQUENCY 计算元素出现概率ifisa(vec