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Statistics report
Jan. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 82
Paper Published : 1209
No. of Authors : 3038
  Journal Paper

Paper Title
Lossy Image Compression Using An Enhanced EZW Algorithm

Abstract
Image compression is been widely used in research for many years and also used in many applications. The main aim of compression is to reduce the requirement of bandwidth for memory and transmission for storage of all types of data. The main objective is to implement the operations utilized in a lossy compression two dimensional images. This paper focuses on developing efficient and effective algorithm for compressing a lossy image using an enhanced Embedded Zero- tree Wavelet (EZW) algorithm. This algorithm has the property that the bits in the bit stream are generated sequentially, affording a complete embedded code. It systematically develops the results of compression which are aggressive with almost every wellknown compression algorithms on typical test images. It consists of two separate lists such as dominant list which has coordinates of co-efficient not yet found significant and subordinate list which has magnitudes of co-efficient already found to be significant. By using lossy compression, multi-level wavelet decomposition methods to select more effective color transformation method and cost determination criteria, so as to further enhance compression performance. To analyze compression performance by multi-level wavelet decomposition methods in order to select more effective color transformation method and cost determinant criteria. An energy aggregation and correlated features of image wavelet coefficient is evaluated using EWLCA using Hilbert curve and singular decomposition into wavelet. The results can be simulated using MATLAB tool. The simulation result reveals that compressed image is good and also have high compression ratio. Keywords— Lossy compression, EZW algorithm, multi-level wavelet decomposition, Hilbert curve, Singular decomposition.


Author - Vennamaneni Vivekananda Rao, Srinivas. T

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| Published on 2016-06-04
   
   
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