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Using Discrete Cosine Transform 2 to achieve High Peak Signal-to-Noise Ratio in Image Processing

by C. Rajeswari, S. Prakasam
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 10
Year of Publication: 2014
Authors: C. Rajeswari, S. Prakasam
10.5120/17221-7460

C. Rajeswari, S. Prakasam . Using Discrete Cosine Transform 2 to achieve High Peak Signal-to-Noise Ratio in Image Processing. International Journal of Computer Applications. 98, 10 ( July 2014), 34-38. DOI=10.5120/17221-7460

@article{ 10.5120/17221-7460,
author = { C. Rajeswari, S. Prakasam },
title = { Using Discrete Cosine Transform 2 to achieve High Peak Signal-to-Noise Ratio in Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 10 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number10/17221-7460/ },
doi = { 10.5120/17221-7460 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:25:51.864975+05:30
%A C. Rajeswari
%A S. Prakasam
%T Using Discrete Cosine Transform 2 to achieve High Peak Signal-to-Noise Ratio in Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 10
%P 34-38
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image compression is the most important process in image Processing. Image compression is one of the process is to reduce redundant information. In Image Compression, the two methods are Lossless Image Compression and Lossy Image Compression. Mostly Lossy image compression is used in Video Conferencing and Video Chat applications. In DCT2 process, the compressed image quality is based on coefficient values. The PSNR values are almost lies in the range between 40 and 50 dB. Compression ratio of compressed image and input image is above 50%. The quality of output compressed image is also good in quality.

References
  1. Ankit Garg, Akshat Agrawal, Ashish Negi , Jan 2014, Vol 85 . No 4, " A Review on Fractal Image Compression " IJCA.
  2. Shrey Kumar G. , Bhavsar, Hardik N. , Mewada, Jan 2014, VI: 85-No: 14, "Comparative Analysis of Various Color Image Compression Techniques" IJCA.
  3. Rajeswari C. , Babu, Venkatesan , July 2013, VI:73 No:14, " Ananlysis of MPC Image Compression using DCT2 in Matlab", IJCA.
  4. Preet Kumar, Geetu Lalit, Aug 2012, Vol. 1, "Comparative Analysis of DCT, DWT and LWT for Image Compression", IJITEE.
  5. Dinesh Gupta, Pardeep Singh, Nivedita, Sugandha Sharma, Vol. 12 No. 2, "A Comparative study of Image Compression between Singular value decomposition, Block truncating coding, Discrete cosine transfer and Wavelet" IJCSNS
  6. Prabhakar Telagarapu, A. Lakshmi Prasanthi, G. Vijaya Santhi, "VI: 4-No. 3" Image Compression Using DCT and Wavelet Transforamation" IJSIP (Sep 2011).
  7. Anilkumar Katheritiya, Swati Patel, Mahesh Goyani "VI: 1-No: 2," in Comparative Analysis between DCT & DWT Techniques of Image Compression", IJEA (2011).
  8. Kiran Bindu, "VI: 2 (2012) "A Hybrid Image Compression Scheme Using DCT and Fractal Image Compression", Himachal Pradesh University, IJORCS, pp-37-42.
  9. Maneesha Gupta, Dr. Ameet Kumar Garg, VI: 2 "Analysis of Image Compression Algorithm Using DCT", 2012, pp. 515-521.
  10. Harjeetpal singh, Sakhi Sharma, VI: 2 (2012), "Hybrid Image Compression Using DWT, DCT & Huffman Encoding Techniques", IJETAE Punjab Technical University.
  11. Prabhakar Telagarapu, A. Lakshmi Prasanthi, G. Vijaya Santhi, "VI: 4-No. 3" Image Compression Using DCT and Wavelet Transforamation" IJSIP (Sep 2011).
  12. Maneesha Gupta, Dr. Ameet Kumar Garg, 2012, "Analysis of Image Compression Algorithm Using DCT", pp. 515-521.
  13. Er. Ramandeep, 2012 , " Image Compression Using Discrete Cosine Transform and Discrete Wavelet Transform", ISSN: 2229-6166
  14. Harjeetpal singh, Sakhi Sharma, 2012, "Hybrid Image Compression Using DWT, DCT & Huffman Encoding Techniques", Vol. No. 2, IJETAE, Punjab Technical University.
  15. ChandanRawat, SukadevMeher, 2011, "A Hybrid Image Compression Scheme Using DCT and Fractal Image Compression" IAJIT
  16. R. Uma, 2011, "FPGA Implementation of 2-D DCT for JPEG Image Compression", IJAEST, Vol. No. 7, Issue No. 1, 001-009.
  17. T. Fryza, S. Hanus, 2003, "Image Compression Algorithms Optimized for MATLAB" Vol. 12 No. 4
  18. NageswaraRaoThoto, 2008, "Image Compression Using Discrete Cosine Transform" Nalanda Institute of Engineering & Technology.
  19. Anton Obukhov, Alexander Kharlamov, 2008, "Discrete Cosine Transform for 8x8Blocks with CUDA"
  20. Meena B. Vallakati1 and Dr. R. R. Sedamkar, 2012, "Low Complexity DCT-based DSC approach for Hyper spectral Image Compression with Arithmetic Code" IJCSI, Vol. No. 9, Issue 5, Thakur college of Engineering and Technology.
  21. D. Malarvizhi and Dr. K. Kuppusamy , 2012,"A New Entropy Encoding Algorithm For Image Compression Using DCT", IJETT, Vol. 3 Issue 3 ISSN: 2231-5381, Alagappa University.
Index Terms

Computer Science
Information Sciences

Keywords

DCT2 Compression ratio Histogram PSNR and Matlab

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