Medical image compression using b-splines and vector quantization

Javad Alirezaie; John A. Robinson

doi:10.1117/12.185908

16 September 1994 Medical image compression using b-splines and vector quantization

Javad Alirezaie, John A. Robinson

Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/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.

Citation Download Citation

Javad Alirezaie and John A. Robinson "Medical image compression using b-splines and vector quantization", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); https://doi.org/10.1117/12.185908

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