Comparative Study & Hybrid Technique for Biomidical Image Compression

The objective of this study is to maximize the compression ratio while preserving images information. The study has considered a set of images from both medical and biometric modalities. The dataset is subjected to four compression techniques which include both lossless and lossy techniques. The lossless techniques are Huffman and Arithmetic. The lossy techniques are Discrete Cosine Transform and Wavelet Transform. The maximum compression ratio for each image is chosen by three experts (for the medical dataset); while an identification software is used for biometric dataset. The next enhancement is done by isolating the region of interest in the image then applying the compression procedure. The last enhancement is the hybrid process which combines the lossless compression technique for the essential regions, and the lossy compression technique for the nonessential regions.This could be done using object segmentation procedure and quad tree decomposition (QTD) as preprocessing steps for the compression process.

Autorentext

Eng. Mohamed Nagy has obtained his master degree in Biomedical Engineering from Cairo University in 2011. he worked as a Clinical Engineer at Suez Canal Authority from 2006 till 2010. he is a Teaching Assistant in Biomedical Engineering Department, Faculty of Engineering, Misr University for Science & Technology (MUST).