Three space-economical algorithms for calculating minimum-redundancy prefix codes

The minimum-redundancy prefix code problem is to determine, for a given list W=[/spl omega//sub 1/,..., /spl omega//sub n/] of n positive symbol weights, a list L=[l/sub 1/,...,l/sub n/] of n corresponding integer codeword lengths such that /spl Sigma//sub i=1//sup n/ 2/sup -li//spl les/1 and /spl Sigma//sub i=1//sup n/ /spl omega//sub i/l/sub i/ is minimized. Let us consider the case where W is already sorted. In this case, the output list L can be represented by a list M=[m/sub 1/,..., m/sub H/], where m/sub l/, for l=1,...,H, denotes the multiplicity of the codeword length l in L and H is the length of the greatest codeword. Fortunately, H is proved to be O(min(log(1/p/sub 1/),n)), where p/sub 1/ is the smallest symbol probability, given by /spl omega//sub 1///spl Sigma//sub i=1//sup n/ /spl omega//sub i/. We present the Fast LazyHuff (F-LazyHuff), the Economical LazyHuff (E-LazyHuff), and the Best LazyHuff (B-LazyHuff) algorithms. F-LazyHuff runs in O(n) time but requires O(min(H/sup 2/, n)) additional space. On the other hand, E-LazyHuff runs in O(n+nlog(n/H)) time, requiring only O(H) additional space. Finally, B-LazyHuff asymptotically overcomes, the previous algorithms, requiring only O(n) time and O(H) additional space. Moreover, our three algorithms have the advantage of not writing over the input buffer during code calculation, a feature that is very useful in some applications.