16 September 1994 Medical image compression using b-splines and vector quantization
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Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994); doi: 10.1117/12.185908
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States
Abstract
A lossy image compression technique, incorporating least squares cubic spline pyramids, vector quantization, predictive coding and arithmetic coding was developed for the compression and reconstruction of Magnetic Resonance Images. Typical results of 29.76 dB Peak Signal-to-Noise ratio (PSNR) for 0.45 bits per pixel (bpp) compression, and 27.91 dB PSNR for 0.33 bpp, compare very favorably with other, recently reported, medical image compression results. Furthermore, block artifacts are absent from the recovered pictures.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Javad Alirezaie, John A. Robinson, "Medical image compression using b-splines and vector quantization", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185908; https://doi.org/10.1117/12.185908
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KEYWORDS
Image compression

Medical imaging

Quantization

Magnetic resonance imaging

Data communications

Data storage

Magnetism

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