Huffman coding is a lossless data compression algorithm. The idea is to assign variable-legth codes to input characters, lengths of the assigned codes are based on the frequencies of corresponding characters. The most frequent character gets the smallest code and the least frequent character gets the largest code.
The variable-length codes assigned to input characters are Prefix Codes, means the codes (bit sequences) are assigned in such a way that the code assigned to one character is not prefix of code assigned to any other character. This is how Huffman Coding makes sure that there is no ambiguity when decoding the generated bit stream.
Applications
Huffman coding today is often used as a "back-end" to some other compression methods. DEFLATE (PKZIP's algorithm) and multimedia codecs such as JPEG and MP3 have a front-end model and quantization followed by Huffman coding (or variable-length prefix-free codes with a similar structure, although perhaps not necessarily designed by using Huffman's algorithm[clarification needed]).
Also read http://nayuki.eigenstate.org/page/huffman-coding-java
Read full article from Greedy Algorithms | Set 3 (Huffman Coding) | GeeksforGeeks
The variable-length codes assigned to input characters are Prefix Codes, means the codes (bit sequences) are assigned in such a way that the code assigned to one character is not prefix of code assigned to any other character. This is how Huffman Coding makes sure that there is no ambiguity when decoding the generated bit stream.
Applications
Huffman coding today is often used as a "back-end" to some other compression methods. DEFLATE (PKZIP's algorithm) and multimedia codecs such as JPEG and MP3 have a front-end model and quantization followed by Huffman coding (or variable-length prefix-free codes with a similar structure, although perhaps not necessarily designed by using Huffman's algorithm[clarification needed]).
Steps to build Huffman Tree
Input is array of unique characters along with their frequency of occurrences and output is Huffman Tree.
Input is array of unique characters along with their frequency of occurrences and output is Huffman Tree.
1. Create a leaf node for each unique character and build a min heap of all leaf nodes (Min Heap is used as a priority queue. The value of frequency field is used to compare two nodes in min heap. Initially, the least frequent character is at root)
2. Extract two nodes with the minimum frequency from the min heap.
3. Create a new internal node with frequency equal to the sum of the two nodes frequencies. Make the first extracted node as its left child and the other extracted node as its right child. Add this node to the min heap.
4. Repeat steps#2 and #3 until the heap contains only one node. The remaining node is the root node and the tree is complete
Steps to print codes from Huffman Tree:
Traverse the tree formed starting from the root. Maintain an auxiliary array. While moving to the left child, write 0 to the array. While moving to the right child, write 1 to the array. Print the array when a leaf node is encountered.
Traverse the tree formed starting from the root. Maintain an auxiliary array. While moving to the left child, write 0 to the array. While moving to the right child, write 1 to the array. Print the array when a leaf node is encountered.
Java Implementation from http://rosettacode.org/wiki/Huffman_coding#Java
abstract class HuffmanTree implements Comparable<HuffmanTree> { public final int frequency; // the frequency of this tree public HuffmanTree(int freq) { frequency = freq; } // compares on the frequency public int compareTo(HuffmanTree tree) { return frequency - tree.frequency; } } class HuffmanLeaf extends HuffmanTree { public final char value; // the character this leaf represents public HuffmanLeaf(int freq, char val) { super(freq); value = val; } } class HuffmanNode extends HuffmanTree { public final HuffmanTree left, right; // subtrees public HuffmanNode(HuffmanTree l, HuffmanTree r) { super(l.frequency + r.frequency); left = l; right = r; } } public class HuffmanCode { // input is an array of frequencies, indexed by character code public static HuffmanTree buildTree(int[] charFreqs) { PriorityQueue<HuffmanTree> trees = new PriorityQueue<HuffmanTree>(); // initially, we have a forest of leaves // one for each non-empty character for (int i = 0; i < charFreqs.length; i++) if (charFreqs[i] > 0) trees.offer(new HuffmanLeaf(charFreqs[i], (char)i)); assert trees.size() > 0; // loop until there is only one tree left while (trees.size() > 1) { // two trees with least frequency HuffmanTree a = trees.poll(); HuffmanTree b = trees.poll(); // put into new node and re-insert into queue trees.offer(new HuffmanNode(a, b)); } return trees.poll(); } public static void printCodes(HuffmanTree tree, StringBuffer prefix) { assert tree != null; if (tree instanceof HuffmanLeaf) { HuffmanLeaf leaf = (HuffmanLeaf)tree; // print out character, frequency, and code for this leaf (which is just the prefix) System.out.println(leaf.value + "\t" + leaf.frequency + "\t" + prefix); } else if (tree instanceof HuffmanNode) { HuffmanNode node = (HuffmanNode)tree; // traverse left prefix.append('0'); printCodes(node.left, prefix); prefix.deleteCharAt(prefix.length()-1); // traverse right prefix.append('1'); printCodes(node.right, prefix); prefix.deleteCharAt(prefix.length()-1); } }
Read full article from Greedy Algorithms | Set 3 (Huffman Coding) | GeeksforGeeks
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