Conference Proceeding

Statistical Analysis of Difference image for Absolutely Lossless Compression of Medical Images

Coll. of Signals, Nat. Univ. of Sci. & Technol.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 10/2006; DOI:10.1109/IEMBS.2006.260427 pp.4767 - 4770 In proceeding of: Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Source: IEEE Xplore

ABSTRACT Absolutely lossless compression technique has been recently proposed for medical image compression. It is a hybrid of lossless and lossy compression for medical images using difference image. It is a multi step process in which we have used lossy coding followed by difference image coding. The combination of two compression ratios is resultant. In this paper we analyze statistics associated with difference image. The main objective of this work is to exploit some statistical measures for a difference image to compress it losslessly. Difference image statistics plays a vital role in our technique to get maximum compression ratios. Proposed scheme is simple, computationally economical and can achieve higher compression ratios than existing standard lossless compression techniques and also meets the legal requirement of medical image archiving

0 0
 · 
0 Bookmarks
 · 
29 Views
  • Source
    Article: An Efficient Low Complexity Lossless Coding Algorithm for Medical Images
    Ghrare S.E, M.A. Mohd. Ali, Jumari K, Ismail M
    [show abstract] [hide abstract]
    ABSTRACT: Problem statement: Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices, the movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve and transmit the volume of digital images. Thus digital image data compression is necessary in order to solve this problem. So in a wide range of medical applications such as disease diagnostic and during the compression process, the loss of information is unacceptable; hence medical images are required to be at high resolution as possible. Instead of lossy compression with relatively high compression ratio, mathematical lossless compression methods are favored in this field. Approach: In this study, an efficient new lossless image coding algorithm using a simple technique was presented. Our coding algorithm was based on pixel redundancy reduction by formulating two matrices only, which were Gray Scale Matrix (GSM) and Binary Matrix (BM). These matrices had been used for coding and decoding processes. Results: Results showed that the maximum compression ratio achieved using the proposed method was 4:1, which was more efficient than the present lossless techniques, moreover the computational complexity is greatly simplified; therefore producing very fast coding and decoding. Conclusion: This algorithm was most suitable for those images where lossy compression was avoided such as medical images used for teleradiology and other telemedicine purposed and it can be applied to other medical modalities.
    American Journal of Applied Sciences. 01/2009;
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.

Keywords

compress
 
compression ratios
 
computationally economical
 
difference image
 
difference image coding
 
Difference image statistics
 
higher compression ratios
 
lossless
 
lossless compression technique
 
lossy compression
 
main objective
 
maximum compression ratios
 
medical image archiving
 
medical image compression
 
medical images
 
Proposed scheme
 
standard lossless compression techniques
 
statistical measures
 
vital role