CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

JPEG Image Compression using DCT and DHT and Comparison of Both Techniques based on Mean Square Error and Peak Signal to Noise Ratio

by Dhananjay Patel, Alina Menoth Jose, Nigel Mascarenhas, Steape Stany Monis
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 15
Year of Publication: 2013
Authors: Dhananjay Patel, Alina Menoth Jose, Nigel Mascarenhas, Steape Stany Monis
10.5120/14200-2418

Dhananjay Patel, Alina Menoth Jose, Nigel Mascarenhas, Steape Stany Monis . JPEG Image Compression using DCT and DHT and Comparison of Both Techniques based on Mean Square Error and Peak Signal to Noise Ratio. International Journal of Computer Applications. 81, 15 ( November 2013), 23-27. DOI=10.5120/14200-2418

@article{ 10.5120/14200-2418,
author = { Dhananjay Patel, Alina Menoth Jose, Nigel Mascarenhas, Steape Stany Monis },
title = { JPEG Image Compression using DCT and DHT and Comparison of Both Techniques based on Mean Square Error and Peak Signal to Noise Ratio },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 15 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number15/14200-2418/ },
doi = { 10.5120/14200-2418 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:09.318475+05:30
%A Dhananjay Patel
%A Alina Menoth Jose
%A Nigel Mascarenhas
%A Steape Stany Monis
%T JPEG Image Compression using DCT and DHT and Comparison of Both Techniques based on Mean Square Error and Peak Signal to Noise Ratio
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 15
%P 23-27
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

DCT based JPEG compression is a widely used standard for lossy image compression. DCT concentrates energy into lower order coefficients. It removes redundancy between neighbouring pixels which leads to uncorrelated transform coefficients which can be encoded independently. There is high computational complexity in DCT. DHT is a real valued transform whose forward and inverse transforms are same except for a an inclusion of a scale factor in the inverse transform. DHT reduces the computational complexity of JPEG compared to DCT. DHT doesn't require a dequantizer at the decoder, since a new quantization technique known as energy quantization is used. It speeds up the encoding procedure, reduces hardware as well as makes the implementation simpler. The quality of the reconstructed image is very good which is verified using MATLAB i. e. the PSNR is improved and the MSE is reduced.

References
  1. Gopal Lakhani, Optical Huffman coding of DCT Blocks IEEE transactions on circuits and systems for video technology, VOL. 14,NO. 4,April 2004.
  2. En-hui Yang,Fellow, IEEE and Longji Wang, Joint Optimization Of Run-Length Coding, Huffman Coding, and Quantization Table with Complete Baseline JPEG Decoder Compatibility, IEEE transactions on image processing, VOL. 18,NO. 1,JANUARY 2009.
  3. Gopal Lakhani,Modified JPEG Huffman Coding IEEE transactions on Image Processing, VOL. 12, NO. 2, February 2003.
  4. D. Malarvizhi, Dr. K. Kuppusamy, A New Entrophy Encoding Algorithm For Image Compression Using DCT, International Journal of Engineering Trends and Technology- Volume3Issue3- 2012.
  5. Maneesha Gupta, Dr. Amit Kumar Garg ,Analysis Of Image Compression Algorithm Using DCT, International Journal of Engineering Research and Applications (IJERA), Vol. 2, Issue 1, Jan-Feb 2012,pp. 515-521.
  6. H. S. Hou, "The fast Hartley Transform algorithm", IEEE Trans. on Computer, vol. 36, no. 2, pp. 147-156, Feb. 1987.
  7. Sorensen ,Jones, Burrus, Heideman, "Computing the discrete Hartley transform",Acoustics,Speech and Signal Processing,IEEE transactions,Vol. 33.
  8. Sharma,Agarwal,Pati,Mohapatr,a2-D Separablediscrete Hartley transform architecture for efficient FPGA resource,Iinternational Coference on Computer And Communication Technology,2010
  9. Sai Lakshmi Kumari N, U. Pradeep Kumar, K. V. Ramana Rao, Implementation of 2D Hartley transform using Distributed Arithmetic, International Journal of Innovative Technology and Exploring Engineering (IJITEE), Volume-1, Issue-5, October 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Discrete Cosine Transform (DCT) Discrete Hartley Transform (DHT) Joint Photographic Experts Group (JPEG) Quantization Encoding Peak Signal to Noise Ratio(PSNR) Mean Square Error(MSE)

Powered by PhDFocusTM