Paper
4 January 2002 Embedded morphological dilation coding for 2D and 3D images
Author Affiliations +
Proceedings Volume 4671, Visual Communications and Image Processing 2002; (2002) https://doi.org/10.1117/12.453015
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
Current wavelet-based image coders obtain high performance thanks to the identification and the exploitation of the statistical properties of natural images in the transformed domain. Zerotree-based algorithms, as Embedded Zerotree Wavelets (EZW) and Set Partitioning In Hierarchical Trees (SPIHT), offer high Rate-Distortion (RD) coding performance and low computational complexity by exploiting statistical dependencies among insignificant coefficients on hierarchical subband structures. Another possible approach tries to predict the clusters of significant coefficients by means of some form of morphological dilation. An example of a morphology-based coder is the Significance-Linked Connected Component Analysis (SLCCA) that has shown performance which are comparable to the zerotree-based coders but is not embedded. A new embedded bit-plane coder is proposed here based on morphological dilation of significant coefficients and context based arithmetic coding. The algorithm is able to exploit both intra-band and inter-band statistical dependencies among wavelet significant coefficients. Moreover, the same approach is used both for two and three-dimensional wavelet-based image compression. Finally we the algorithms are tested on some 2D images and on a medical volume, by comparing the RD results to those obtained with the state-of-the-art wavelet-based coders.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fabio Lazzaroni, Alberto Signoroni, and Riccardo Leonardi "Embedded morphological dilation coding for 2D and 3D images", Proc. SPIE 4671, Visual Communications and Image Processing 2002, (4 January 2002); https://doi.org/10.1117/12.453015
Lens.org Logo
CITATIONS
Cited by 8 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Wavelets

3D image processing

Image compression

Linear filtering

Skull

Statistical analysis

3D applications

Back to Top