An Alternate Way to Develop Lossless Graphical Data Compression Package using Non-Linear Single Cycle Multiple Attractor Cellular Automata

Compression is one of the major topics in the field of research as it is used for storing data in a lesser storage space of the repository. Compression is furthermore required in case of sending data from source to destination through network (internet or intranet). The time required is less in case of sending fewer amounts of data. So, compression is a necessity for transmission of original huge data as a modified small amount of data with a low overhead. Image compression is the application of data compression on digital images. This research work takes into consideration an image as the source file (.bmp) and converts it to the standard PNM format and further in plain PNM format (raw file) to utilize the binary format specification used in PNM. Single Cycle Multiple Attractor Cellular Automata (SMACA) is used as a compression tool. The results achieved through experimentation are based on lossless image compression. The first pass compresses the PNM image using SMACA based techniques followed by the second pass which utilizes Huffman variable length encoding scheme. Initially, 31% (approx.) & 95% (approx.) compression ratio are achieved using SMACA structure on the PNM & raw files respectively. Final compressed data of the image obtained achieves a further compression by 6% over the previous compressed data using the Huffman algorithm.