Title :
VQ index coding for high-fidelity medical image compression
Author :
Jiang, Wen ; Wu, Xiaolin ; Ng, Wai Yin
Author_Institution :
Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Abstract :
In order to obtain the high-fidelity medical compressed images, a new compression scheme is proposed. Based on the stringent requirements on lossy medical image compression, we refine the context modeling for a given class of medical images and utilize the conditional entropy coding of the VQ index (CECOVI) scheme to code the MR head images. The experimental results show that the image-type-dependent CECOVI can achieve better rate-distortion performance than the state-of-art wavelet image coder SPIHT. This also implies that incorporating the conditional entropy coding strategy into the VQ process is an appropriate way for high-fidelity medical image compression
Keywords :
biomedical NMR; brain; diagnostic radiography; entropy codes; image coding; medical image processing; rate distortion theory; vector quantisation; MR head images; MRI; SPIHT; VQ index coding; brain images; conditional entropy coding; context modeling; experimental results; high-fidelity medical image compression; image-type-dependent CECOVI; lossy image compression; probability estimation; rate-distortion performance; wavelet image coder; Application software; Biomedical imaging; Entropy coding; Image coding; Image reconstruction; Image storage; Medical diagnostic imaging; Medical services; Rate-distortion; Space technology;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.632212