Compression of Medical   Images Based on 2D-Discrete Cosine Transform and Vector Quantization Algorithms

Azuwam Ali Alhadi

doi:10.58916/jhas.v8i3.151

Authors

Azuwam Ali Alhadi Department of Communication Engineering, College of Electronic Technology, Bani-Walid, Libya Author

DOI:

https://doi.org/10.58916/jhas.v8i3.151

Keywords:

PSNR, JPEG, DCT, Compression Ratio, CT

Abstract

Abstract: In this paper, two types of Medical images which were collected from CT scan and Ultrasound system in order to reduce the number of bits needed to represent a medical image with preservation of image quality. Medical imaging has a great impact on diagnosis of diseases and preparation to surgery. On the other hand, the storage and transmission is an important issue due to massive size of medical image data. For example, each slice of CT images is 512 by 512, and the data set consists of 200 to 400 images leading to 150 MB of data in average .An efficient compression of the medical data can solve the storage and transmission problem. Medical images are compressed using proposed algorithm that includes two techniques which are discrete cosine transform DCT and Vector Quantization VQ. The paper started from collecting Medical images, and developing compression algorithms by DCT-QV using MATLAB and evaluate the performance of these techniques by measuring the difference between the original image and compressed images using Peak Signal to Noise Ratio PSNR, mean square error MSE, compression ratio CR, and bit per pixel BPP and. Experimental results show that proposed algorithm produces a high quality for compressed images with acceptable compression rate in terms quantization level is more than 30%.

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