High Rate Squeezing using LL Band Coding in Wavelet Domain
M. Santhosh
Dr. M. Santhosh, Associate Professor, Anurag Group of Institutions, Venkatapur Ghatkesar Hyderabad (Telangana), India.

Manuscript received on 15 August 2019 | Revised Manuscript received on 27 August 2019 | Manuscript Published on 06 September 2019 | PP: 102-111 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F10220886S19/19©BEIESP | DOI: 10.35940/ijeat.F1022.0886S19
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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: Wavelet based image compression standards not only inspired signal and image processing community but also the research community of many research and application fields towards the wavelet theory. All wavelet based schemes follow the standard sequence of steps. They are transformation and the processing task at one end followed by the inverse of processing task and inverse transform at another end. Wavelet based compression was done in a quite different manner from its inception. The early techniques include Embedded Zerotree Wavelet (EZW) coding and Set Partitioning in Hierarchical Trees (SPIHT) coding. Although, SPIHT is an extension of EZW, both follow more or less similar process in coding and decoding. These schemes code the significant and insignificant coefficients using symbols or maintaining a list of indices of the coefficients. The decision on significant or insignificant will be taken by comparing with a threshold which will be updated in each iteration. In both the schemes, if a coefficient is identified as an insignificant one, then the bits incurred in conveying this coefficient is less and in many cases very less. One can imagine that if a coefficient is made to be an insignificant then the number of bits required will be less. This issue was taken up in this paper and bits of selected regions is chosen and a significant improvement is compression ratio is observed at a little cost of quality.
Keywords: EZW, Significance Map, SPIHT, Wavelet Based Compression.
Scope of the Article: Software Domain Modelling and Analysis