Code Compression Using Variable-to-fixed Coding Based on Arithmetic Coding

Embedded computing systems are space and cost sensitive; memory is one of the most restricted resources, posing serious constraints on program size. Code compression, which is a special case of data compression where the input source is machine instructions, has been proposed as a solution to this problem. Previous work in code compression has focused on either fixed-to-variable coding or dictionary-based algorithms. We propose code compression schemes that use variable-to-fixed (V2F) length coding, based on arithmetic coding. Experiments show that the compression ratio using memoryless V2F coding for the TMS320C6x processor is on average 82.5% (defined as the ratio of the compressed over the uncompressed program) and decompression can be parallelized. A Markov-based V2F coding based on arithmetic coding, can achieve an average compression ratio 72% for TMS320C6x, while decompression cannot be parallelized. Furthermore, our experiments have shown that arithmetic coding based V2F codin...

• Type: Conference
• Year: 2003
• Where: DCC
• Authors: Yuan Xie, Wayne Wolf, Haris Lekatsas
• Keywords: Arithmetic Coding, Average Compression Ratio, Computer Graphics, DCC 2003, V2F Coding Scheme