A comparative analysis on the wavelet-based image compression techniques
As the coming era of digitized image information, it is critical to produce high compression performance while minimizing the amount of image data so the data can be stored effectively. Compression using wavelet algorithm is one of the indispensable techniques to solve this problem. The Wavelet Algo...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Published: |
2013
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6241/ http://eprints.uthm.edu.my/6241/1/A%2DComparative%2DAnalysis%2Don%2Dthe%2DWavelet%2DBased%2DImage%2DCompression%2DTechniques.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | As the coming era of digitized image information, it is critical to produce high compression performance while
minimizing the amount of image data so the data can be stored effectively. Compression using wavelet algorithm is one of the
indispensable techniques to solve this problem. The Wavelet Algorithm contains transformation process, quantization process,
and lossy entropy coding. Wavelets are functions which allow data analysis of signals or images, according to scales or
resolutions and it provides a powerful and remarkably flexible set of tools for handling fundamental problems in science and
engineering, such signal compression, image de-noising, image enhancement and image recognition. The aim of this paper is
to compare the image quality by using 4 wavelet-based image compression techniques; namely Set Partitioning In Hierarchical
Trees (SPIHT), Embedded Zerotree Wavelet (EZW), Wavelet Difference Reduction (WDR) and Adaptively Scanned Wavelet
Difference Reduction (ASWDR). While for analysis, Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE),
Compression Ratio (CR) and Bit Per Pixels (BPP) analysis are used. From the obtained results, it shows that WDR outperform
in terms of compression efficiency. |
|---|