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DICOM image compression using Bilinear interpolation

Authors: R. Nadarajan; G. Uma Vetri Selvi;

DICOM image compression using Bilinear interpolation

Abstract

In this paper, we propose a new lossy image compression algorithm for DICOM ( Digital Imaging and Communications in Medicine) images using Bilinear interpolation. This method presents a technique for classification of the image blocks on the basis of threshold value of variance. The image is divided into [m×n] blocks. Depending on the variance, the block is classified as significant or insignificant. The corner pixels of the blocks are stored and the remaining pixels are obtained by bilinear interpolation.The difference between the original and interpolated image is calculated and the difference is transmitted along with corner pixels and header data. At the receiving end, images are reconstructed with corner pixels. The difference is added only to the significant blocks. The experimental results shows that the proposed technique yields better performance by yielding good compression ratio and PSNR which is much desired in medical images.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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