Title :
Compression of medical image using vector quantization
Author :
Phanprasit, Tanasak
Author_Institution :
Dept. of Electr. & Electron. Eng., Bangkok Univ., Bangkok, Thailand
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;
Conference_Titel :
Biomedical Engineering International Conference (BMEiCON), 2013 6th
Conference_Location :
Amphur Muang
Print_ISBN :
978-1-4799-1466-1
DOI :
10.1109/BMEiCon.2013.6687718
