Special Issue Article
Lossless Compression and Efficient Reconstruction of Colour Medical Images
|M.Suganya1, A.Ramachandran2, D.Venugopal3 and A.Sivanantha Raja4
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The information from patient’s body is captured as medical images and is used for surgical and diagnostic purposes. Compression of medical images is essential for storage and transmission of patient's data. Due to high impact of details in medical images, lossless compression is preferred. This paper presents colour medical image compression using Curvelet transform with lifting and Huffman coding. It also presents the decompression using inverse transforms and the performance is analysed using subjective and objective quality metrics. Most transforms though well suited to point singularities have limitations with orientation selectivity and do not represent two-dimensional singularities and also smooth curves are not represented effectively. The Curvelet transform is well suited for colour medical images which are normally having curvy portions. Various medical images such as MRI, CT, etc are compressed for different image sizes and the results are analysed using compression ratio, PSNR, bits per pixel value, mean square error, structural correlation, normalized correlation and average difference.