- Title
- Towards a low complexity scheme for medical images in scalable video coding
- Creator
- Shoaib, Muhammad; Imran, Muhammad; Subhan, Fazli; Ahmad, Iftikhar
- Date
- 2020
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/185413
- Identifier
- vital:16681
- Identifier
-
https://doi.org/10.1109/ACCESS.2020.2976715
- Identifier
- ISBN:2169-3536 (ISSN)
- Abstract
- Medical imaging has become of vital importance for diagnosing diseases and conducting noninvasive procedures. Advances in eHealth applications are challenged by the fact that Digital Imaging and Communications in Medicine (DICOM) requires high-resolution images, thereby increasing their size and the associated computational complexity, particularly when these images are communicated over IP and wireless networks. Therefore, medical research requires an efficient coding technique to achieve high-quality and low-complexity images with error-resilient features. In this study, we propose an improved coding scheme that exploits the content features of encoded videos with low complexity combined with flexible macroblock ordering for error resilience. We identify the homogeneous region in which the search for optimal macroblock modes is early terminated. For non-homogeneous regions, the integration of smaller blocks is employed only if the vector difference is less than the threshold. Results confirm that the proposed technique achieves a considerable performance improvement compared with existing schemes in terms of reducing the computational complexity without compromising the bit-rate and peak signal-to-noise ratio. © 2013 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- IEEE Access Vol. 8, no. (2020), p. 41439-41451
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright @ IEEE
- Rights
- Open Access
- Subject
- 40 Engineering; 46 Information and computing sciences; eHealth; Flexible macroblock ordering; Low complexity; Medical imaging; Scalable video coding; Slice coding
- Full Text
- Reviewed
- Funder
- This work was supported by the Deanship of Scientific Research, King Saud University, under Grant RG-1435-051.
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