Compression of CT Images with Branched Inverse Pyramidal Decomposition
In this chapter a new approach is suggested for compression of CT images with branched inverse pyramidal decomposition. A packet of CT images is analyzed and the correlation between each couple inside it is found. Then the packet is split into groups of images with almost even correlation, typically into six or more. One is chosen as a referent being mostly correlated with all of the others. From the rest difference images with the referent are found. After the pyramidal decomposition a packet of spectral coefficients is formed and difference levels which are coded by entropy coder. Scalable high compression is achieved at higher image quality in comparison to that of the JPEG2000 coder. The proposed approach is considered perspective also for compression of MRI images.
KeywordsCT image Compression Branched inverse pyramidal decomposition
This chapter was supported by the Joint Research Project Bulgaria-Romania (2010–2012): “Electronic Health Records for the Next Generation Medical Decision Support in Romanian and Bulgarian National Healthcare Systems”, DNTS 02/19.
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