- Title
- Lossless image coding using binary tree decomposition of prediction residuals
- Creator
- Ali, Mortuza; Murshed, Manzur; Shahriyar, Shampa; Paul, Manoranjan
- Date
- 2015
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/98758
- Identifier
- vital:10283
- Identifier
-
https://doi.org/10.1109/PCS.2015.7170074
- Abstract
- State-of-the-art lossless image compression schemes, such as, JPEG-LS and CALIC, have been proposed in the context adaptive predictive coding framework. These schemes involve a prediction step followed by context adaptive entropy coding of the residuals. It can be observed that there exist significant spatial correlation among the residuals after prediction. The efficient schemes proposed in the literature rely on context adaptive entropy coding to exploit this spatial correlation. In this paper, we propose an alternative approach to exploit this spatial correlation. The proposed scheme also involves a prediction stage. However, we resort to a binary tree based hierarchical decomposition technique to efficiently exploit the spatial correlation. On a set of standard test images, the proposed scheme, using the same predictor as JPEG-LS, achieved an overall compression gain of 2.1% against JPEG-LS. © 2015 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Rights
- Copyright © 2015 IEEE
- Rights
- This metadata is freely available under a CCO license
- Subject
- Data compression; Image coding; Entropy; Lossless image compression schemes; JPEG-LS; CALIC
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