Evaluation of JPEG-2000 Image Compression as Applied to Electroencephalography

Abstract

In this paper we present an experiment utilizing the JPEG-2000 image compression standard to compress multi-channel electroencephalographic (EEG) signals at a lossless quality. We employ multiple pre-processing methods and assess their performance based on achieved compression ratio, computational demand, feature set, and complexity relative to existing methods from several related published works. We propose a simple pre-processing method that arranges multi-channel EEG matrices into a blocked form which yields an average 2.267:1 lossless compression ratio for the Brain Computer Interface IV-1 (BCICIV-1) dataset.