Modified Discrete Wavelet Transformation to Compress DICOM Medical Images with Run-Length Encoding

Abstract

With rapid advancements in medical imaging technology, a substantial amount of image data has been produced to assist clinical diagnostics. Nevertheless, storing and transmitting medical images with high-resolution content presents a formidable challenge that needs to be addressed. This study proposes a technique to compress DICOM images using a Modified variant of Discrete Wavelet Transform (MDWT) including RunLength Encoding and DEFLATE algorithm. The proposed mechanism decomposes a DICOM image into its frequency sub-bands, namely, approximation (LL), horizontal detail (LH), vertical detail (HL), and diagonal detail (HH) coefficients which are then thresholded and quantized in an adaptive manner using uniform scalar quantization. The quantized coefficients a re run-length encoded with a modified s cheme t o t raverse t he d ata including linear, diagonal, and spiral approaches. Subsequently, DEFLATE algorithm-based compression is performed for further reduction in data volume. Results indicate a noteworthy improvement in compression ratio with the modifications while preserving a high level of detail.