Compression of medical image using vector quantization

Author

Phanprasit, Tanasak

Author_Institution

Dept. of Electr. & Electron. Eng., Bangkok Univ., Bangkok, Thailand

fYear

2013

fDate

23-25 Oct. 2013

Firstpage

1

Lastpage

4

Abstract

Medical image compression is necessary to store the huge database in Medical Centres and medical data transfer for the purpose of diagnosis. This paper attempts to improve the higher peak signal to noise ratio (PSNR) by using the system error compensation (SEC) method. The SEC design is based on quantization and curvelet transform (CT) decomposes the system error (E) to six scales. Only the scale 1 and scale 6 are constructed to error compensation. The simulation results are shown that the proposed method can improve 40.48 %, 9.69 % both in terms of bit rate and PSNR when compared to the conventional method.

Keywords

curvelet transforms; data compression; error compensation; image coding; medical image processing; PSNR; curvelet transform; medical centres; medical data transfer; medical image compression; peak signal to noise ratio; system error compensation method; vector quantization; Algorithm design and analysis; Biomedical imaging; Error compensation; Image coding; Image reconstruction; PSNR; Transforms; Curvelet Transform; Discrete Wavelet Transform; Fuzzy C-Means; Support Vector Machine; Vector Quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering International Conference (BMEiCON), 2013 6th

Conference_Location

Amphur Muang

Print_ISBN

978-1-4799-1466-1

Type

conf

DOI

10.1109/BMEiCon.2013.6687718

Filename

6687718