首页 > 代码库 > huffman编码——原理与实现
huffman编码——原理与实现
哈夫曼算法原理
Wikipedia上面说的非常清楚了,这里我就不再赘述,直接贴过来了。
1952年, David A. Huffman提出了一个不同的算法,这个算法能够为不论什么的可能性提供出一个理想的树。香农-范诺编码(Shanno-Fano)是从树的根节点到叶子节点所进行的的编码,哈夫曼编码算法却是从相反的方向,暨从叶子节点到根节点的方向编码的。
- 为每一个符号建立一个叶子节点,并加上其对应的发生频率
- 当有一个以上的节点存在时,进行下列循环:
- 把这些节点作为带权值的二叉树的根节点,左右子树为空
- 选择两棵根结点权值最小的树作为左右子树构造一棵新的二叉树,且至新的二叉树的根结点的权值为其左右子树上根结点的权值之和。
- 把权值最小的两个根节点移除
- 将新的二叉树增加队列中.
- 最后剩下的节点暨为根节点,此时二叉树已经完毕。
演示样例
Huffman Algorithm
符号 A B C D E 计数 15 7 6 6 5 概率 0.38461538 0.17948718 0.15384615 0.15384615 0.12820513
在这样的情况下,D,E的最低频率和分配分别为0和1,分组结合概率的0.28205128。如今最低的一双是B和C,所以他们就分配0和1组合结合概率的0.33333333在一起。这使得BC和DE所以0和1的前面加上他们的代码和它们结合的概率最低。然后离开仅仅是一个和BCDE,当中有前缀分别为0和1,然后结合。这使我们与一个单一的节点,我们的算法是完整的。
可得A代码的代码长度是1比特,其余字符是3比特。
字符 A B C D E 代码 0 100 101 110 111
Entropy:
Pseudo-code
1: begin
2: count frequencies of single characters (source units)
3: output(frequencies using Fibonacci Codes of degree 2)
4: sort them to non-decreasing sequence
5: create a leaf node (character, frequency c, left son = NULL, right son = NULL)
6: of the tree for each character and put nodes into queue F
7: while (|F|>=2) do
8: begin
9: pop the first two nodes (u1, u2) with the lowest
10: frequencies from sorted queue
11: create a node evaluated with sum of the chosen units,
12: successors are chosen units (eps, c(u1)+c(u2), u1, u2)
13: insert new node into queue
14: end
15: node evaluate with way from root to leaf node (left son 1, right son 0)
16: create output from coded intput characters
17: end
哈夫曼算法实现
实现的时候我们用vector<bool>记录每一个char的编码;用map<char,vector<bool>>表示整个字典;
就得到了以下的代码(以下有两个,一对一错):
先放出来这个错的,以示警戒:
/************************************************************************/ /* File Name: Huffman.cpp * @Function: Lossless Compression @Author: Sophia Zhang @Create Time: 2012-9-26 10:40 @Last Modify: 2012-9-26 11:10 */ /************************************************************************/ #include"iostream" #include "queue" #include "map" #include "string" #include "iterator" #include "vector" #include "algorithm" using namespace std; #define NChar 8 //suppose use at most 8 bits to describe all symbols #define Nsymbols 1<<NChar //can describe 256 symbols totally (include a-z, A-Z) typedef vector<bool> Huff_code;//8 bit code of one char map<char,Huff_code> Huff_Dic; //huffman coding dictionary class HTree { public : HTree* left; HTree* right; char ch; int weight; HTree(){left = right = NULL; weight=0;} HTree(HTree* l,HTree* r,int w,char c){left = l; right = r; weight=w; ch=c;} ~HTree(){delete left; delete right;} int Getweight(){return weight?weight:left->weight+right->weight;} bool Isleaf(){return !left && !right; } bool operator < (const HTree tr) const { return tr.weight < weight; } }; HTree* BuildTree(int *frequency) { priority_queue<HTree*> QTree; //1st level add characters for (int i=0;i<Nsymbols;i++) { if(frequency[i]) QTree.push(new HTree(NULL,NULL,frequency[i],(char)i)); } //build while (QTree.size()>1) { HTree* lc = QTree.top(); QTree.pop(); HTree* rc = QTree.top(); QTree.pop(); HTree* parent = new HTree(lc,rc,parent->Getweight(),(char)256); QTree.push(parent); } //return tree root return QTree.top(); } void Huffman_Coding(HTree* root, Huff_code& curcode) { if(root->Isleaf()) { Huff_Dic[root->ch] = curcode; return; } Huff_code& lcode = curcode; Huff_code& rcode = curcode; lcode.push_back(false); rcode.push_back(true); Huffman_Coding(root->left,lcode); Huffman_Coding(root->right,rcode); } int main() { int freq[Nsymbols] = {0}; char *str = "this is the string need to be compressed"; //statistic character frequency while (*str!=‘\0‘) freq[*str++]++; //build tree HTree* r = BuildTree(freq); Huff_code nullcode; nullcode.clear(); Huffman_Coding(r,nullcode); for(map<char,Huff_code>::iterator it = Huff_Dic.begin(); it != Huff_Dic.end(); it++) { cout<<(*it).first<<‘\t‘; Huff_code vec_code = (*it).second; for (vector<bool>::iterator vit = vec_code.begin(); vit!=vec_code.end();vit++) { cout<<(*vit)<<endl; } } }
上面这段代码,我执行出来不正确。在调试的时候发现了一个问题,就是QTree优先队列中的排序出了问题,说来也是,上面的代码中,我重载小于号是对HTree object做的;而实际上我建树时用的是指针,那么优先级队列中元素为指针时该怎么办呢?
那我们将friend bool operator >(Node node1,Node node2)改动为friend bool operator >(Node* node1,Node* node2),也就是传递的是Node的指针行不行呢?
答案是不能够,由于依据c++primer中重载操作符中讲的“程序猿仅仅能为类类型或枚举类型的操作数定义重载操作符,在把操作符声明为类的成员时,至少有一个类或枚举类型的參数依照值或者引用的方式传递”,也就是说friend bool operator >(Node* node1,Node* node2)形參中都是指针类型的是不能够的。我们仅仅能再建一个类,用当中的重载()操作符作为优先队列的比較函数。
就得到了以下正确的代码:
/************************************************************************/ /* File Name: Huffman.cpp * @Function: Lossless Compression @Author: Sophia Zhang @Create Time: 2012-9-26 10:40 @Last Modify: 2012-9-26 12:10 */ /************************************************************************/ #include"iostream" #include "queue" #include "map" #include "string" #include "iterator" #include "vector" #include "algorithm" using namespace std; #define NChar 8 //suppose use 8 bits to describe all symbols #define Nsymbols 1<<NChar //can describe 256 symbols totally (include a-z, A-Z) typedef vector<bool> Huff_code;//8 bit code of one char map<char,Huff_code> Huff_Dic; //huffman coding dictionary /************************************************************************/ /* Tree Class elements: *2 child trees *character and frequency of current node */ /************************************************************************/ class HTree { public : HTree* left; HTree* right; char ch; int weight; HTree(){left = right = NULL; weight=0;ch =‘\0‘;} HTree(HTree* l,HTree* r,int w,char c){left = l; right = r; weight=w; ch=c;} ~HTree(){delete left; delete right;} bool Isleaf(){return !left && !right; } }; /************************************************************************/ /* prepare for pointer sorting*/ /*because we cannot use overloading in class HTree directly*/ /************************************************************************/ class Compare_tree { public: bool operator () (HTree* t1, HTree* t2) { return t1->weight> t2->weight; } }; /************************************************************************/ /* use priority queue to build huffman tree*/ /************************************************************************/ HTree* BuildTree(int *frequency) { priority_queue<HTree*,vector<HTree*>,Compare_tree> QTree; //1st level add characters for (int i=0;i<Nsymbols;i++) { if(frequency[i]) QTree.push(new HTree(NULL,NULL,frequency[i],(char)i)); } //build while (QTree.size()>1) { HTree* lc = QTree.top(); QTree.pop(); HTree* rc = QTree.top(); QTree.pop(); HTree* parent = new HTree(lc,rc,lc->weight+rc->weight,(char)256); QTree.push(parent); } //return tree root return QTree.top(); } /************************************************************************/ /* Give Huffman Coding to the Huffman Tree*/ /************************************************************************/ void Huffman_Coding(HTree* root, Huff_code& curcode) { if(root->Isleaf()) { Huff_Dic[root->ch] = curcode; return; } Huff_code lcode = curcode; Huff_code rcode = curcode; lcode.push_back(false); rcode.push_back(true); Huffman_Coding(root->left,lcode); Huffman_Coding(root->right,rcode); } int main() { int freq[Nsymbols] = {0}; char *str = "this is the string need to be compressed"; //statistic character frequency while (*str!=‘\0‘) freq[*str++]++; //build tree HTree* r = BuildTree(freq); Huff_code nullcode; nullcode.clear(); Huffman_Coding(r,nullcode); for(map<char,Huff_code>::iterator it = Huff_Dic.begin(); it != Huff_Dic.end(); it++) { cout<<(*it).first<<‘\t‘; std::copy(it->second.begin(),it->second.end(),std::ostream_iterator<bool>(cout)); cout<<endl; } }
Reference:
1. http://www.binaryessence.com/dct/en000042.htm
2. http://zh.wikipedia.org/zh/%E9%A6%99%E5%86%9C-%E8%8C%83%E8%AF%BA%E7%BC%96%E7%A0%81#.E5.93.88.E5.A4.AB.E6.9B.BC.E7.AE.97.E6.B3.95
3. http://www.stringology.org/DataCompression/sh/index_en.html
关于Compression很多其它的学习资料将继续更新,敬请关注本博客和新浪微博Sophia_qing。
声明:以上内容来自用户投稿及互联网公开渠道收集整理发布,本网站不拥有所有权,未作人工编辑处理,也不承担相关法律责任,若内容有误或涉及侵权可进行投诉: 投诉/举报 工作人员会在5个工作日内联系你,一经查实,本站将立刻删除涉嫌侵权内容。