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Analysis of Wavelet-based Transform Compression Techniques on Medical Image

A. O. Ajao, T. S. Ibiyemi Published in Image Processing

International Journal of Applied Information Systems
Year of Publication: 2015
© 2015 by IJAIS Journal
10.5120/ijais15-451403
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  1. A O Ajao and T S Ibiyemi. Article: Analysis of Wavelet-based Transform Compression Techniques on Medical Image. International Journal of Applied Information Systems 9(4):64-68, July 2015. BibTeX

    @article{key:article,
    	author = "A. O. Ajao and T. S. Ibiyemi",
    	title = "Article: Analysis of Wavelet-based Transform Compression Techniques on Medical Image",
    	journal = "International Journal of Applied Information Systems",
    	year = 2015,
    	volume = 9,
    	number = 4,
    	pages = "64-68",
    	month = "July",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

This paper is aimed at analyzing the performance of three different state-of-the-art image compression schemes namely Embedded Zerotree Wavelet (EZW), Spatial-orientation Trees Wavelet (STW) and Set Partitioning in Hierarchical Trees (SPHIT). The paper analyses the compression schemes using X-ray image data such that the quality of the reconstructed image would be closely related to its original image after 20 iterations of the compression steps. We compared the compression ratio and bit per pixel against the peak signal to noise ratio respectively for X-ray images represented in various image sizes of 256x256 and 512x512. Also, we discussed the characteristics on quality performance used. Some tests conducted for comparing them and the compression quality are addressed in this paper and the quality of compression is determined from the metrics of compression ratio (CR), bit per pixel (BPP), mean square error (MSE) and peak signal to noise ratio (PSNR).

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Keywords

Compression, X-ray Images, Discreet Wavelet Transform, Bit-rate.