Mapping Based Lossless Data Compression Technique

Data compression has a high impact on the storage and transmission of data. An efficient technique is yet to be developed. In this paper, a novel compression technique is shown to compress the binary data. This paper presents a symbol arranged in a perfect N-ary tree and compression is carried out in the presence of a combination of all alphabet structured on a tree. To arrange data, it is shown the construction of symbols using the perfect tree. Using the tree, all the combinations of data are arranged in the world plane. The world plane data is for the reduction of the original data to the lowest possible bit. The paper demonstrates that the average compression ratio for one segment mechanism, directly compresses from the world plane data using direct mapping. To optimize the compression, the paper shows a novel segmentation approach by segment mapping technique to reduce the size of the data. Furthermore, we have presented reducing data from the three-segment mechanism and reconstructed the original data without loss of any information. In the reconstruction of data, the paper demonstrates the reverse mapping technique by mapping the fly value to the base value. We obtain the fly value from the codeword by separating the segment location and the fly value. On obtaining the fly value, we use remapping of the actual node location. Once the node location is obtained, we traverse a tree to obtain the original data in sequence. The experiment is carried out on one bit symbol size and compared with Huffman's data compression technique.