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Dimensional scalable lossless compression of MRI images using haar wavelet lifting scheme with EBCOT
Author(s) -
Anusuya V.,
Srinivasa Raghavan V.
Publication year - 2014
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.22092
Subject(s) - computer science , discrete wavelet transform , lossless compression , image compression , wavelet , artificial intelligence , set partitioning in hierarchical trees , lifting scheme , haar wavelet , discrete cosine transform , computer vision , algorithm , wavelet transform , second generation wavelet transform , data compression , pattern recognition (psychology) , image processing , image (mathematics)
Modern medical imaging requires storage of large quantities of digitized clinical data. To provide high bandwidth and to reduce the storage space, a medical image must be compressed before transmission. One of the best image compression techniques is using the Haar wavelet transform. The method of discrete cosine transform (DCT) is chosen to be the preprocessing scheme to identify the image frequency information and has excellent energy compaction property. The block coding algorithm uses a wavelet transform to generate the sub band samples, which can be quantized and coded. It is more robust to errors than many other wavelet‐based schemes. In this article, simulations are carried out on different medical Images and it demonstrates the performance in terms of peak signal to noise ratio (PSNR) & bits per pixel (BPP). Our proposed method is found to preserve information fidelity while reducing the amount of data. © 2014 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 24, 175–181, 2014