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Image Compression: Combination of Discrete Transformation and Matrix Reduction

M.A. Anwer1 , D.A. Anwar2 , S.A. Anwer3

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-1 , Page no. 1-6, Jan-2017

Online published on Jan 31, 2017

Copyright © M.A. Anwer, D.A. Anwar , S.A. Anwer . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: M.A. Anwer, D.A. Anwar , S.A. Anwer , “Image Compression: Combination of Discrete Transformation and Matrix Reduction,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.1-6, 2017.

MLA Style Citation: M.A. Anwer, D.A. Anwar , S.A. Anwer "Image Compression: Combination of Discrete Transformation and Matrix Reduction." International Journal of Computer Sciences and Engineering 5.1 (2017): 1-6.

APA Style Citation: M.A. Anwer, D.A. Anwar , S.A. Anwer , (2017). Image Compression: Combination of Discrete Transformation and Matrix Reduction. International Journal of Computer Sciences and Engineering, 5(1), 1-6.

BibTex Style Citation:
@article{Anwer_2017,
author = {M.A. Anwer, D.A. Anwar , S.A. Anwer },
title = {Image Compression: Combination of Discrete Transformation and Matrix Reduction},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2017},
volume = {5},
Issue = {1},
month = {1},
year = {2017},
issn = {2347-2693},
pages = {1-6},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1146},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1146
TI - Image Compression: Combination of Discrete Transformation and Matrix Reduction
T2 - International Journal of Computer Sciences and Engineering
AU - M.A. Anwer, D.A. Anwar , S.A. Anwer
PY - 2017
DA - 2017/01/31
PB - IJCSE, Indore, INDIA
SP - 1-6
IS - 1
VL - 5
SN - 2347-2693
ER -

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Abstract

Nowadays, compressing large data using different compression methods increase rapidly. This explains the recent importance and popularity of compressing data of multimedia applications as well as wavelet transforms in this field. Wavelet transforms tend to benefit of block-based transforms, including the Discrete Cosine Trans-form (DCT). DCT is responsible for displaying blocking artifacts while wavelets have compact support and can offer a DCT an adaptable substitute to DCT. The popularity of single-wavelets, formed through converting and expanding of single approximation functions as well as detail functions, offered high multi-resolution function-approximation bases. This paper discusses the idea of the image compression using two levels DWT with two-dimensional DCT on every 8x8 block. Hence, the low-frequency sub-band is reduced. The DC-Column stores the DC-coefficients. As a result of using Huffman coding the DC-Column will be coded. Meanwhile the other AC-Coefficient has to be quantized in order to gain additional zeros, allowing it to be converted easily to bits through the Huffman coding. HL2, HH2, as well as LH2 are other high-frequencies coefficients that are coded using the Minimize-Matrix-Size Algorithm. The mentioned proposed algorithm converts the three high-frequency coefficients into a single real number. Nevertheless, the use of the proposed algorithm; one-dimensional-array that has many real values will be reduced and will be converted it to many bits. The results of the compression algorithm are based on Mean Square Error ( MSE).

Key-Words / Index Term

Minimize Matrix Size; Huffman Coding; DWT; DCT

References

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