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INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
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ISSN: 2321-9939 | ESTD Year: 2013

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Paper Title
Image Compression Decompression using Polynomial Based Wavelet Transformation in PDF Document
Authors
  D.Selvanayagi,  Dr.S.Pannirselvam

Abstract
Image compression technique is a request of data compression on digital images which encodes the original image with few bits. The intended of image compression is used to minimizing the redundancy of the picture and to keep or broadcast information in an efficient manner. It is carried out the problem of minimizing the huge data needed to characterize a digital image. In PDF application, extraction of images becomes more highly required to analyze the image content. But, the Lossless Compression is insufficient to measure the correlation amid the images and the DCT is not efficiently considered. The sparse representation of double discrete wavelet transform (DDWT) is a generative method of image blur that determines wavelet analysis of a blurred image. The DDWT offers less reliable for identifying object motion blur. Then, presented an image decomposition model is used to reduce the noise in the images but is less optimization provided. Then, High quality, noise removed image contents are stored in image file and subjected for image compression and decompression in PDCT-LIC technique. Finally, Polynomial Discrete Cosine Transformation Lossless Image Compression (PDCT-LIC) technique is developed to improve compression ratio, quicker compression/ decompression time, reduce compressed file size and minimize information loss.

Keywords- DCT, PCDCT-LIC, DDWT
Publication Details
Unique Identification Number - IJEDR1702136
Page Number(s) - 820-826
Pubished in - Volume 5 | Issue 2 | May 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  D.Selvanayagi,  Dr.S.Pannirselvam,   "Image Compression Decompression using Polynomial Based Wavelet Transformation in PDF Document", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.820-826, May 2017, Available at :http://www.ijedr.org/papers/IJEDR1702136.pdf
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