Feb 9. Huffman Encoding

Prefix Free Encoding

Suppose we wish to encode a set of letters \mathcal{A}=\{a_1, \cdots, a_N\} in binary such that  we can unambiguously decode a binary stream into  \mathcal{A}. One possibility is to use a prefix free encoding. An encoding is prefix free if the code word for any a_i is not the prefix of the code word for any other a_j.

Huffman Encoding

Suppose we are given the set \mathcal{A} together with their frequencies \{f_1, \cdots, f_N\}. We wish to find a prefix free code such that total length of the code when used with these frequencies is minimized . Such a code is called a Huffman encoding of the set \mathcal{A}.

Suppose we assign a code word c_i to every s_i and let b_i = |c_i|. Then we wish to minimize \min \sum_{i=1}^N f_i b_i.

Observation: A prefix code maps to a full binary tree. One can see this by considering the tree where the left child of a node corresponds to a 0 and the right child corresponds to a 1. The a_i  corresponds to a leaf in this tree and the code-word c_i for a_i corresponds to the labels on the unique path from the root to s_i, while b_i is the depth of s_i in this tree. We will call such a tree T a prefix tree. Note that the cost c(T) of T is given by c(T) = \sum_{i=1}^N f_i*depth_T(a_i).

Greedy Algorithm for Finding a Huffman Encoding

Consider the following greedy algorithm for computing a Huffman encoding:

  • Sort the letters according to their frequency so that f_1 \ge f_2 \ge \cdots \ge f_N.
  • Pick a_{N-1} and a_N to have a common parent a_{N-1}a_N with frequency f_{N-1} + f_N.
  • Iterate till only one element is left

Lemma: There exists an optimal tree that combines a_{N-1} and a_N and they have maximum depth in this tree.

Proof: Let T be an optimal prefix tree. Since T is a full tree it has at least two leaves of maximum depth.  Let a_i and a_j be two leaves. If a_N is not one of them then swap a_i with a_N (if a_i \neq a_N). Similarly swap a_j with a_{N-1} if a_{N-1} is not in \{a_i, a_j\}. Note that the cost of this tree T' can only be lower than T since a_{N-1}, a_N are the least frequent items.

Lemma: Let T be an optimal tree for \mathcal{A} = \{a_1,\cdots, a_N\}with frequencies \{f_1,\cdots, f_N\} and let T' be an optimal tree for \mathcal{A}' = \{a_1, \cdots, a_{N-1}a_N\}  with frequencies \{f_1,\cdots, f_{N-2}, f_{N-1} + f_N\}.  Then T' is a subtree of T.

Proof: Let T' be the tree where we delete the leaves a_{N-1} and a_N and assign a_{N-1}a_N to the parent of a_{N-1} and a_N in T. Note that c(T') = c(T) - f_{N-1} - f_N.  We claim that T' must be an optimal tree for \mathcal{A}' . Suppose not, and let \tilde{T} be an optimal tree for \mathcal{A}'. Then add two leaves a_{N-1} and a_N to the node corresponding to a_{N-1}a_N in \tilde{T} to get the tree \tilde{T}'. Note that c(\tilde{T}') = c(\tilde{T}) + f_{N-1} + f_N < c(T') + f_{N-1} +f_N = c(T). This contradicts the optimality of T for \mathcal{A}.



  1. I also think it is better if we have questions to practice. The questions on the test are very different from questions we did for homework. I don’t know how to prepare for the test. Could you assign problems for exam 2 from textbook?


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