Encoding of CT Image by Predicting PSNR Based on LSSVM

Author

Zi-Rong Lin ; Xin-Yu Jin ; Chang-Yong Zhao

Author_Institution

Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China

fYear

2013

fDate

16-17 Nov. 2013

Firstpage

50

Lastpage

53

Abstract

With the development of remote telemedicine, the research of medical image compression with limited band is very important. In this paper, we analyze the features of kidney CT image and build LSSVM model to predict PSNR of ROI(Region of Interest) and BR(Background Region) of CT image. Then we propose a new method of encoding of CT image by predicting PSNR based on LSSVM, which has lower computational complexity and improves about 1/3 in encoding efficiency compared to the ROI encoding algorithm based on ISA-DWT. Besides, it can also achieve the effect of balancing ROI and BR as ISA-DWT algorithm.

Keywords

computerised tomography; data compression; image coding; least squares approximations; medical image processing; support vector machines; telemedicine; BR; CT image encoding; ISA-DWT algorithm; LSSVM; PSNR; ROI; Region of Interest; background region; least square support vector machines; medical image compression; remote telemedicine; Computed tomography; Encoding; Image coding; PSNR; Prediction algorithms; Predictive models; Support vector machines; CT image; LSSVM; PSNR; ROI; image compression;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology and Applications (ITA), 2013 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4799-2876-7

Type

conf

DOI

10.1109/ITA.2013.18

Filename

6709934