An efficient bit-wise source encoding technique based on source mapping

In this paper, we propose an efficient source encoding technique based on mapping a non-binary information source with a large alphabet onto an equivalent binary source using weighted fixed-length code assignments. The weighted codes are chosen such that the entropy of the resulting binary source multiplied by the code length is made as close as possible to that of the original non-binary source. It is found that a large saving in complexity, execution time, and memory size is achieved when the commonly-used source encoding algorithms are applied to the n^th order extension of the resulting binary source. This saving is due to the large reduction in the number of symbols in the alphabet of the new extended binary source. As an example to validate the effectiveness of this approach, text compression using Huffman encoder applied to the n^th order extended binary source is studied. It is found that the bit-wise Huffman encoder of the 4th-order extended binary source (16 symbols) achieves compression efficiency close to that of the conventional Huffman encoder (256 symbols)