Strategy of Microscopic Parallelism for Bitplane Image Coding

Francesc Auli-Llinas, Pablo Enfedaque, Juan C. Moure, Ian Blanes, Victor Sanchez

Research output: Contribution to journalArticleResearchpeer-review

5 Citations (Scopus)


Recent years have seen the upraising of a new type of processors strongly relying on the Single Instruction, Multiple Data (SIMD) architectural principle. The main idea behind SIMD computing is to apply a flow of instructions to multiple pieces of data in parallel and synchronously. This permits the execution of thousands of operations in parallel, achieving higher computational performance than with traditional Multiple Instruction, Multiple Data (MIMD) architectures. The level of parallelism required in SIMD computing can only be achieved in image coding systems via microscopic parallel strategies that code multiple coefficients in parallel. Until now, the only way to achieve microscopic parallelism in bit plane coding engines was by executing multiple coding passes in parallel. Such a strategy does not suit well SIMD computing because each thread executes different instructions. This paper introduces the first bit plane coding engine devised for the fine grain of parallelism required in SIMD computing. Its main insight is to allow parallel coefficient processing in a coding pass. Experimental tests show coding performance results similar to those of JPEG2000.

Original languageAmerican English
Pages (from-to)163-172
Number of pages10
JournalData Compression Conference Proceedings
Publication statusPublished - 2 Jul 2015


  • Bitplane image coding
  • JPEG2000
  • single instruction multiple data


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