Non-Uniform Quantized Huffman Compression Technique for EEG Data

In this paper, We propose a hybrid compression technique by integrating the Discrete Cosine Transform (DCT) and a Non-Uniform Quantized Huffman in order to minimize the Electroencephalography (EEG) data size. Therefore, to get a high compression ratio we apply the lossy compression followed by a lossless compression algorithm. We use DCT encoder followed by either non-uniform quantized Huffman (NonUQH) coding or Run Length Encoding (RLE) then compare between them. The system performance is evaluated in terms of the compression/decompression time, the compression ratio, and the root mean square error. The proposed hybrid technique DCT/NonUQH achieves 90% compression compared to 59% by DCT/RLE with the same similarity. Furthermore, it needs 50% less time for compression/decompression process.