Modified Arithmetic Coding to Increase the Compression Rate of Text Data

In the past two decades, hardware and software have advanced quickly due to technological advancement. Global data distribution and storage have become simpler as a result. However, the bandwidth cannot handle the volume of information being created. As a result, researchers are now looking into data compression. Numerous data compression techniques have been developed, including Shannon Fano, Huffman, Lempel Ziv, and Arithmetic coding techniques. Characters are typically expressed in ASCII code using a predetermined number of bits per character. Lossless data compression uses an entropy coding method called Arithmetic Coding (AC). In the arithmetic encoding of a string similar to Huffman coding, symbols seen frequently are encoded with more bits than symbols seen less frequently. Unlike other entropy encoding techniques like Huffman coding, a single arbitrary-precision fraction between 0 and 1 encodes the entire message in arithmetic coding. In this proposed method, the arbitrary-precision fraction is converted into its equivalent binary form, split into groups of 8 bits, and converted into its identical UTF-8-character set, whose length is far lower than the arbitrary-precision fraction. Huffman code is used to compress further the UTF-8 character set.