Huffman编码的Matlab实现

1、clear allfprintf( Reading data 、 ) data=imread( cameraman 、 tif );data=uint8(data); %读入数据 , 并将数据限制为 uint8 fprintf( 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 ) %测试就是否无失真

2、isOK=isequal(data(:),unzipped(:) %显示压缩效果 whos data zipped unzipped function zipped,info=norm2huff(vector) if isa(vector, uint8 ),error( input argument must be a uint8 vector ) end vector=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=s

3、ot(f);simbols=simbols(sortindex);%产生码字 generate the codeword as the 52 bits of a double len=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(i

4、ndex2)=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 , 就是两个节点的频率尽量与前一个节点的频率想当asresort data in order to have two nodes with lower frequency first to f,sortindex=sort(f);simbols_index=simbols_index(sortindex);end%对应相应的元素与码字 codewo

5、rd=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

6、;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、人(0:23);maxcodelen=0;for index 1:length(codeword), len=length(codewordindex);if lenmaxcodelen,maxcodelen=l

7、en;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、人(0:7);zipped=uint8(weights*double(string);%存储一个稀疏矩阵huffcodes=sparse(1,1); % init sparse mat

8、rixfor 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

9、(codeword_old),codeword_newindex=item codeword_oldindex;endfunction vector=huff2norm(zipped,info)%HUFF2N0RM Huffma 解码器%HUFF2N0RM(X,INF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if isa(zipped, uint8 ),error( input argument must be a uint8 vector)end%产生 01序列len=length(zipped);string=repmat(uint8(0),1,

10、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、A(0:51);vector=repmat(uint8(0),1,info,length);vectorindex=1;codeindex=1;code=0;for index=1:len,code=bitset(co

11、de,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;endendfunction byte=decode(code,info) byte=info 、 huffcodes(code);function f=frequency(vector)%FREQUENCY算元素出现概率if isa(vector, u