A Parallel Quadtree Approach for Image Compression using Wavelets

Authors: Hamed Vahdat Nejad, Hossein Deldari

Abstract:

Wavelet transforms are multiresolution decompositions that can be used to analyze signals and images. Image compression is one of major applications of wavelet transforms in image processing. It is considered as one of the most powerful methods that provides a high compression ratio. However, its implementation is very time-consuming. At the other hand, parallel computing technologies are an efficient method for image compression using wavelets. In this paper, we propose a parallel wavelet compression algorithm based on quadtrees. We implement the algorithm using MatlabMPI (a parallel, message passing version of Matlab), and compute its isoefficiency function, and show that it is scalable. Our experimental results confirm the efficiency of the algorithm also.

Keywords: Image compression, MPI, Parallel computing, Wavelets.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075290

References:

[1] Jeremy Kepner, "Parallel programming with MatlabMPI", 2002, High Performance Embedded Computing (HPEC) workshop, MIT Lincoln Laboratory, Lexington, MA, http://arXiv.org/abs/astro-ph/0107406.
[2] P. Moravie, H. Essafi, C. Lambert-nebout, and J-L. Basille, "Real-time image compression using SIMD architectures", In Proceedings of Computer Architectures for Machine Perception, 1995.
[3] Rafael C. Gonzalez and Richard E. Woods, "Digital Image Processing", Addison-Wesley Publishing Company.
[4] S. Khanfir, M. Jemni ,and E. Ben Braiek, "Parallelization of an image compression and decompression algorithm based on 1D wavelet transformation", In Proceedings of First International Symposium on Control, communications and Signal Processing, 2004.
[5] Shi-xin Sun, Chao-yang Pang, Wen-yu Chen, "A new parallel architecture for image compression", In Proceedings of CSCW in Design, 2002.
[6] Yansun Xu , John B. Weaver, Dennis M. Healy, and Jian Lu, "Wavelet transform domain filters: A spatially selective noise filtration technique", In Proceedings of IEEE Tansactions on image processing, Vol. 3, No. 6, November 1994.
[7] "Message Passing Interface" (MPI), http://www.mpiforum.org