AI Article Synopsis
- The paper presents a joint source-channel coding system aimed at achieving lossless compression and maintaining the integrity of medical data in low-quality networks.
- It utilizes advanced techniques like scalable coding, locally adapted resolution (LAR), and the Mojette transform to meet these goals.
- The implementation is detailed in the paper, along with a performance evaluation comparing it to standard CALIC coding and the use of Reed-Solomon codes for error protection.
Article Abstract
The joint source-channel coding system proposed in this paper has two aims: lossless compression with a progressive mode and the integrity of medical data, which takes into account the priorities of the image and the properties of a network with no guaranteed quality of service. In this context, the use of scalable coding, locally adapted resolution (LAR) and a discrete and exact Radon transform, known as the Mojette transform, meets this twofold requirement. In this paper, details of this joint coding implementation are provided as well as a performance evaluation with respect to the reference CALIC coding and to unequal error protection using Reed-Solomon codes.
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| http://dx.doi.org/10.1016/j.compmedimag.2008.01.002 | DOI Listing |
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