Fuzzy Morphology Based JPEG compression for Image Quality Enhancement of Noisy Images
Vanitha Kakollu1 , P Chandrasekhar Reddy2
Section:Research Paper, Product Type: Journal Paper
Volume-6 ,
Issue-9 , Page no. 380-384, Sep-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i9.380384
Online published on Sep 30, 2018
Copyright © Vanitha Kakollu, P Chandrasekhar Reddy . 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.
View this paper at Google Scholar | DPI Digital Library
How to Cite this Paper
- IEEE Citation
- MLA Citation
- APA Citation
- BibTex Citation
- RIS Citation
IEEE Style Citation: Vanitha Kakollu, P Chandrasekhar Reddy, “Fuzzy Morphology Based JPEG compression for Image Quality Enhancement of Noisy Images,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.380-384, 2018.
MLA Style Citation: Vanitha Kakollu, P Chandrasekhar Reddy "Fuzzy Morphology Based JPEG compression for Image Quality Enhancement of Noisy Images." International Journal of Computer Sciences and Engineering 6.9 (2018): 380-384.
APA Style Citation: Vanitha Kakollu, P Chandrasekhar Reddy, (2018). Fuzzy Morphology Based JPEG compression for Image Quality Enhancement of Noisy Images. International Journal of Computer Sciences and Engineering, 6(9), 380-384.
BibTex Style Citation:
@article{Kakollu_2018,
author = {Vanitha Kakollu, P Chandrasekhar Reddy},
title = {Fuzzy Morphology Based JPEG compression for Image Quality Enhancement of Noisy Images},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {380-384},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2877},
doi = {https://doi.org/10.26438/ijcse/v6i9.380384}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.380384}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2877
TI - Fuzzy Morphology Based JPEG compression for Image Quality Enhancement of Noisy Images
T2 - International Journal of Computer Sciences and Engineering
AU - Vanitha Kakollu, P Chandrasekhar Reddy
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 380-384
IS - 9
VL - 6
SN - 2347-2693
ER -
VIEWS | XML | |
449 | 305 downloads | 206 downloads |
Abstract
The extent of communicated information through internet has augmented speedily over the past few years. Image compression is the preeminent way to lessen the size of the image. JPEG is the one the best technique related to lossy image compression. In this paper a novel JPEG compression algorithm with Fuzzy-Morphology techniques was proposed. The efficacy of the proposed algorithm compared to JPEG is presented with metrics like PSNR, MSE, No of bits transmitted. The proposed approaches lessen the number of encoded bits as a result tumbling the quantity of memory needed. The Planned approaches are best appropriate for the images corrupted with Gaussian, Speckle, Poisson, Salt & Pepper noises.
Key-Words / Index Term
Compression, Morphology, PSNR, MSE, RMS
References
[1] Olivier Egger and Wei Li, “VERY LOW BIT RATE IMAGE CODING USING MORPHOLOGICAL OPERATORS AND ADAPTIVE DECOMPOSITIONS” IEEE International Conference on Image Processing Vol-3, PP No.326-330, Nov 1994.
[2] Ricardo L. de Queiroz, Member IEEE, “Processing JPEG-Compressed Images and Documents” IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 7, NO. 12, PPNo: 1661-1672, DECEMBER 1998.
[3] Ravi Prakash, IEEE Member, Joan L. Mitchell, IEEE Fellow, and David A. Stepneski, “Enhanced JPEG Compression of Documents” IEEE International Conference on Image Processing Vol-3, PP No: 494-497, Oct-2001.
[4] Bai Xiangzhi, Zhou Fugen, “Edge Detection Based on Mathematical Morphology and Iterative Thresholding” IEEE International Conference on Image Processing Vol-2, PP No: 1849-1852, Nov-2006.
[5] Sreelekha G and P.S.Sathidevi, “An Improved JPEG Compression Scheme Using Human Visual System Model” IEEE, PP No: 98-101, June 2007.
[6] Ch. Ramesh, N.B.Venkateswarlu and J.V.R Murthy, “Filter Augmented JPEG Compressions” IJCA, Vol-60, No-17, PP No: 1-5, Dec-2012.
[7] Marlapalli Krishna, G.Srinivas and Prasad Reddy PVGD” Image Smoothening and Morphological operators Based JPEG Compression”, JATIT+, Vol.85, No.3, PPNo: 252-259, March 2016.
[8] Marlapalli Krishna, Prasad Reddy PVGD and G.Srinivas “ A Smoothening based JPEG Compression for an Objective Image Quality Enhancement of Regular and Noisy Images, IJAER, Vol.11, No.6, PPNo:3799-3804, 2016.
[9] G.Srinivas,P.Naga Srinivasu, T.Srinivasa rao and Ch.Ramesh “Harmonic and Contra Harmonic Mean Centric JPEG Compression for an Objective Image Quality Enhancement of Noisy Images”, Springer , International conference on smart computing and its application PP No143-152, 2017.
[10] G.Srinivas, Prof Prasad Reddy P.V.G.D, and K.ramya “An N-Square Approach for Reduced Complexity Non-Binary Encoding”, GJCST, PP No: 36-39, Vol: XI Issue XI, 2010.
[11] Dillip Ranjan Nayak, Ashutosh Bhoi” Image Enhancement Using Fuzzy Morphology”, Journal of Engineering, Computers & Applied Sciences”, Vol.3,NO.3, pp no:22-24, March 2014.
[12] G. Srinivas, Prasad Reddy P.V.G.D and K. Gayatri Devi, ”N-Square Approach For Lossless Image Compression And Decompression”, GJCST, Vol:10, Issue:9, pp no: 47-49, 2010.