The algorithm yields optimal ternary codes Steps to build Huffman Tree
Input is array of unique characters along with their frequency of occurrences and output is Huffman Tree.


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)
Extract two nodes with the minimum frequency from the min heap.
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.
Repeat steps#2 and #3 until the heap contains only one node. The remaining node is the root node and the tree is complete.


If we would like to generalize the Huffman algorithm for coded words in ternary system (i.e. coded words using the symbols 0 , 1 and 2 ) I think that we could do it as follows.

Steps to build Huffman Tree
Input is array of unique characters along with their frequency of occurrences and output is Huffman Tree.


Create a leaf node for each unique character and build a min heap of all leaf nodes 
Extract three nodes with the minimum frequency from the min heap.
Create a new internal node with frequency equal to the sum of the three nodes frequencies. Make the first extracted node as its left child, the second extracted node as its middle child and the third extracted node as its right child. Add this node to the min heap.
Repeat steps#2 and #3 until the heap contains only one node. The remaining node is the root node and the tree is complete.


How can we prove that the algorithm yields optimal ternary codes?
We can’t prove that, but we can disprove it. The given algorithm is not always optimal. In step&nbsp;2, three nodes may not be available, so there is more than one way to build the tree. That can’t happen in the binary case.

Consider a min heap containing four characters, whose frequencies are 0.4, 0.3, 0.2, and 0.1. The given algorithm yields the tree on the left, with mean length 1.6. The optimal tree is shown on the right, mean length 1.3.

@PeterShor’s comment above indicates that a correct algorithm is known, but I haven’t seen it.