Correlative Analysis of EZW and SPIHT Compression Algorithms using Sevenlets Wavelet Technique
B. B. S. Kumar1, P. S. Satyanarayana2

1B.B.S.Kumar*, Ph. D Research Scholar, JU, Bangalore, India.
2Dr. P.S. Satyanarayana, Retd. Professor & HOD, Dept. of ECE, BMSCE, Bangalore, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 10, 2020. | PP: 1099-1104 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2672039520/2020©BEIESP | DOI: 10.35940/ijitee.E2672.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The research is carried out to find wavelets in image processing of CT(computerized Tomography) JPEG(Joint Photographic Experts Group) medical image for a Lossy Compression. The EZW(Embedded Zerotree Wavelet) and SPIHT(Set Partitioning Hierarchical Trees) algorithms method is implemented to identify the quality of image by DWT(Discrete Wavelet Transform). Quality analysis is processed based on parameters measure such as CR(Compression Ratio), BPP(Bits Per Pixel), PSNR( Peak Signal to Noise Ratio) and MSE(Mean Square Error). Comparison is made to justify having a good image retaining for seven wavelets, how they correlation each other. Using seven wavelets as assigned a new term Sevenlets in this research work. Medical images are very significant to retain exact image with minimizing loss of information at retrieving. The algorithms EZW and SPIHT give better support to wavelets for compression analysis, can be used to diagnosis analysis to have better perception of image corrective measure. .
Keywords: CR, CT, DWT, EZW, MSE, PSNR, SPIHT, JPEG and Lossy Compression
Scope of the Article: Parallel and Distributed Algorithms