DocumentCode :
3040660
Title :
Compressing industrial computed tomography images based on stationary wavelet
Author :
Haina Jiang ; Xiangyu Yang ; Li Zeng
Author_Institution :
Key Lab. of Optoelectron. Technol. & Syst. of the Educ. Minist. of China, Chongqing Univ., Chongqing, China
fYear :
2013
fDate :
14-17 July 2013
Firstpage :
124
Lastpage :
127
Abstract :
To have higher resolution and precision, the amount of industrial computed tomography data has become larger and larger. Moreover, industrial computed tomography images are approximately piece-wise constant, which fits for encoding contour. Then, we develop an improved compression method based on wavelet contour coding Firstly, we merge Freeman encoding idea into our IMCE (an improved method for contours extraction based on stationary wavelet) to extract contours. Simultaneously, each contour point extracted by IMCE is directly stored by recording the relative coordinates not the actual ones through exploiting their continuity and logical linking. By that, the two steps of traditional contour-based compression method are simplified into only one. Lastly, Huffman coding is employed to further lossless compress them. Experimental results show that this method can gain good compression ratio as well as keeping ideal quality of decompressed image.
Keywords :
computerised tomography; data compression; feature extraction; image coding; wavelet transforms; Freeman encoding; Huffman coding; IMCE encoding; contour-based compression method; image compression; image precision; image quality; image resolution; improved method for contours extraction; industrial computed tomography image; stationary wavelet transform; Abstracts; Decoding; Encoding; Measurement by laser beam; Optical imaging; PSNR; Transform coding; Contour coding; Image compression; Industrial computed tomography; Stationary wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2013 International Conference on
Conference_Location :
Tianjin
ISSN :
2158-5695
Print_ISBN :
978-1-4799-0415-0
Type :
conf
DOI :
10.1109/ICWAPR.2013.6599303
Filename :
6599303
Link To Document :
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