Compressing industrial computed tomography images by means of contour coding

Haina Jiang; Li Zeng

doi:10.1117/1.JEI.22.4.043017

18 November 2013 Compressing industrial computed tomography images by means of contour coding

Haina Jiang, Li Zeng

Author Affiliations +

Journal of Electronic Imaging, Vol. 22, Issue 4, 043017 (November 2013). https://doi.org/10.1117/1.JEI.22.4.043017

Abstract

An improved method for compressing industrial computed tomography (CT) images is presented. To have higher resolution and precision, the amount of industrial CT data has become larger and larger. Considering that industrial CT images are approximately piece-wise constant, we develop a compression method based on contour coding. The traditional contour-based method for compressing gray images usually needs two steps. The first is contour extraction and then compression, which is negative for compression efficiency. So we merge the Freeman encoding idea into an improved method for two-dimensional contours extraction (2-D-IMCE) to improve the compression efficiency. By exploiting the continuity and logical linking, preliminary contour codes are directly obtained simultaneously with the contour extraction. By that, the two steps of the traditional contour-based compression method are simplified into only one. Finally, Huffman coding is employed to further losslessly compress preliminary contour codes. Experimental results show that this method can obtain a good compression ratio as well as keeping satisfactory quality of compressed images.

Citation Download Citation

Haina Jiang and Li Zeng "Compressing industrial computed tomography images by means of contour coding," Journal of Electronic Imaging 22(4), 043017 (18 November 2013). https://doi.org/10.1117/1.JEI.22.4.043017

Published: 18 November 2013

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KEYWORDS

Image compression

Computed tomography

Computer programming

Image segmentation

Visualization

X-ray computed tomography

Image processing

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