Title :
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
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;
Conference_Titel :
Information Technology and Applications (ITA), 2013 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-2876-7
DOI :
10.1109/ITA.2013.18
