DMCA
Image Compression of medical images using VQ-Huffman Coding Technique
BibTeX
@MISC{Chopra_imagecompression,
author = {Vinay Chopra and Harsimranjeet Kaur and Ap Daviet Jalandhar},
title = {Image Compression of medical images using VQ-Huffman Coding Technique},
year = {}
}
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Abstract
Abstract- Digital Medical Imaging has grown very fast in recent years and hence plays a vital role in diagnosis, treatment, and research area. All the radiological modalities such as CT scanners, MRI, US, PET, X-Ray made by multiple vendors and located at one or many sites can communicate by means of DICOM across an network. Now days, hospitals need to store large volume of data about the patients that require huge hard disk space and high bandwidth. This would employ the need to compress DICOM images for efficient storage and transmission over the internet. In this paper, a new compression algorithm combining the features of both lossy (DCT) and lossless (Huffman Coding) compression techniques has been designed and implemented. The performance of proposed algorithm is then improved using Vector Quantization technique in the context of increasing Compression Ratio as well as preserving the quality of compressed images. Different quality metrics like MSE, PSNR and CR are computed on various medical test images. The experimental results show that proposed compression technique performs better than the existing techniques in terms of performance parameters.
Keyphrases
vq-huffman coding technique medical image image compression many site different quality metric compression technique high bandwidth multiple vendor vector quantization technique vital role huge hard disk space compressed image efficient storage ct scanner compression technique performs new compression radiological modality large volume performance parameter various medical test image recent year huffman coding abstract digital medical imaging compression ratio dicom image experimental result research area
