research-article

A particle swarm optimization method for tuning the parameters of multiscale retinex based color image enhancement

Authors:

M. C. Hanumantharaju,

V. N. Manjunath Aradhya,

M. Ravishankar,

A. MamathaAuthors Info & Claims

ICACCI '12: Proceedings of the International Conference on Advances in Computing, Communications and Informatics

Pages 721 - 727

https://doi.org/10.1145/2345396.2345514

Published: 03 August 2012 Publication History

Abstract

In this paper, a Particle Swarm Optimization (PSO) method for tuning the parameters of multiscale retinex based color image enhancement is presented. The image enhancement using multiscale retinex scheme heavily depends on parameters such as Gaussian surround space constants, number of scales, gain and offset etc. Due to hard selection of these parameters, PSO has been used in order to investigate the optimal parameters for the best image enhancement. The PSO method of parameter tuning adopted for multiscale retinex with modified color restoration (MSRMCR) algorithm achieves very good quality of reconstructed images, far better than that possible with the other existing methods. The presented algorithm is compared with other promising enhancement schemes such as histogram equalization, NASA's multiscale retinex with color restoration (MSRCR), Improved MSRCR (IMSRCR), and Photoflair software. The quality of the enhanced image is validated iteratively using an efficient objective criterion which is based on entropy and edge information of an image. Finally, the quality of the reconstructed images obtained by the proposed method is evaluated using Wavelet Energy (WE) metric. The experimental results presented shows that color image enhanced by the proposed algorithm are clearer, vivid and efficient.

References

[1]

Anil K. Jain, "Fundamentals of Digital Image Processing, Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1989.

Digital Library

[2]

Rafael C. Gonzalez and Richard E. Woods, "Digital Image Processing", 3^rd edition, Prentice-Hall, 2008.

Digital Library

[3]

Zhang YuDong, Wu LeNan, Wang ShuiHua and Wei Geng, "Color Image Enhancement based on HVS and PC Neural Network", Science in China Edition: Information Science, Vol. 53, pp. 1963--1976, 2010.

[4]

Zia-ur Rahman, Glenn A. Woodell and Daniel J. Jobson, "A Comparison of the Multiscale Retinex with other Image Enhancement Techniques", In IS & T's 50^th Annual Conference, A Celebration of All Imaging, Vol. 50, 426--431.

[5]

H. D Cheng and X. J Shi, "A Simple and Effective Histogram Equalization Approach to Image Enhancement", Journal of Digital Signal Processing, Vol. 14, Issue 2, pp. 158--170, 2004.

[6]

Xu Guan, Su Jian, Pan Hongda, Zhang Zhiguo and Gong Haibin, "An Image Enhancement Method Based on Gamma Correction", Proceedings IEEE Second International Symposium on Computational Intelligence and Design, pp.60--63, 2009.

Digital Library

[7]

Ming-Jung Seow and Vijayan K. Asari, "Ratio Rule and Homomorphic Filter for Enhancement of Digital Color Image", Journal of Neurocomputing, Vol. 69, Issue 7-9, pp. 954--958, 2006.

Digital Library

[8]

Daniel J. Jobson, Zia-ur Rahman, and Glenn A Woodell, "A Multiscale Retinex for bridging the gap between color images and the human observation of scenes", IEEE Transaction on Image Processing, Vol. 6, No. 7, pp. 965--976, 1997.

Digital Library

[9]

M. Sundaram, K. Ramar, N. Arumugam, G. Prabin, "Histogram Modified Local Contrast Enhancement for Mammogram Images", Applied Soft Computing, Vol. 11, Issue 8, pp. 5809--5816, 2011.

Digital Library

[10]

Elisabeta Antonia Haller, "Adaptive Histogram Equalization in GIS", Annals of the University of Craiova-Mathematics and Computer Science Series, Vol. 38, No. 1, pp. 100--104, 2011.

[11]

Ho-Hyoung Choi and Byoung-Ju Yun, "Contrast Enhancement for the Captured Image by Estimating Local Illumination", Optical Review, Vol. 18, No. 5, pp. 389--393, 2011.

[12]

Apurba Gorai and Ashish Ghosh, "Gray-level Image Enhancement By Particle Swarm Optimization", World Congress on Nature & Biologically Inspired Computing (NaBIC), pp. 72--77, 2009.

[13]

L. Lucchese and S. K Mitra, "A New Algorithm based on Saturation and Desaturation in the XY chromaticity diagram for enhancement and rendition of color images", Proceedings IEEE International Conference Image Processing, pp. 7--10, 2001.

[14]

V. Buzuloiu, M. Ciuc, R. M Ranayya and C. Vertan, "Adaptive-neighborhood Histogram Equalization of Color Images", Journal of Electron Imaging, Vol. 10, Issue 2, pp. 445--459, 2001.

[15]

Kai-Qi-Huang, Zhenyang Wu, George S. K Fung, Francis H,Y Chan, "Color Image Denoising with Wavelet Thresholding based on Human Visual System Model" Signal Process Image Communication, Vol. 20, Issue 2, pp. 115--127, 2005.

[16]

Glenn Hines, Zia-ur Rahman, Daniel Jobson and Glenn Woodell, "Single Scale Retinex using Digital Signal Processors", Global Signal Processing Conference, 2004.

[17]

M. Z Zhang, M. J. Seow and V. K Asari, "A High Performance Architecture for Color Image Enhancement using a Machine Learning Approach", International Journal of Computational Intelligence Research-Special Issue on Advances in Neural Networks, Vol. 2, No. 1, pp. 40--47, 2006.

[18]

Hiroshi Tsutsui, Hideyuki Nakamura, Ryoji Hashimoto, Hiroyuki Okuhata and Takao Onoye, "An FPGA Implementation of Real-Time Retinex Video Image Enhancement", Proceedings of World Automation Congress (WAC), pp. 1--6, 19-23 Sept., 2010.

[19]

D. Brainard and B. Wandell, "Analysis of the Retinex theory of color vision", Journal of the Optical Society of America, Vol. 3, No. 10, pp. 1651--1661, Oct. 1986.

[20]

Jharna Majumdar, Mili Nandi M and P. Nagabhushan, "Retinex Algorithm with Reduced Halo Artifacts", Defence Science Journal, Vol. 61, No. 6, pp. 559--566, 2011.

[21]

Ruibo Zhang, Yali Huang and Zhen Zhao, "A Ultrasound Liver Image Enhancement AlgorithmBased on Multi-Scale Retinex Theory", 5th International Conference on Bioinformatics and Biomedical Engineering, (iCBBE), pp. 1--3, 2011.

[22]

Liu Yong and Yang Ping Xian, "Multi-dimensional multiscale image enhancement algorithm", 2nd International Conference on Signal Processing Systems (ICSPS), pp. V3-165--V3-168, 2010.

[23]

Tiedong Zhang, Lei Wan, Yuru Xu and Yu Lu, "Sonar Image Enhancement based on Particle Swarm Optimization", 3^rd IEEE, Conference on Industrial Electronics and Applications, pp. 2216--2221, 2008.

[24]

Gao Qinqing, Zeng Guangping, Chen Dexin and He Ketai; "Image Enhancement Technique Based On Improved PSO Algorithm", 6th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 234--238, 2011.

[25]

Chih-Tsung Shen and Wen-Liang Hwang, "Color Image Enhancement using Retinex with Robust Envelop, Proceedings of International Conference on Image Processing (ICIP-2009), 2009.

Digital Library

[26]

N. Kwok, Q. Ha, D. Liu, and G. Fang, "Intensity-Preserving Contrast Enhancement for Gray-Level Images using Multi objective Particle Swarm Optimization", CASE06. IEEE International Conference on Automation Science and Engineering CASE-2006, pp. 21--26, 2006.

[27]

M. C Hanumantharaju, M. Ravishankar, D. R Rameshbabu and S. Ramachandran, "Color Image Enhancement using Multiscale Retinex with Modified Color Restoration Technique", Proceedings of IEEE International Conference on Emerging Applications of Information Technology (EAIT 2011), pp. 93--97, 2011.

Digital Library

[28]

Lu Li, Zhou Yicong, Panetta Karen, Agaian Sos, "Comparative Study of Histogram Equalization Algorithmsfor Image Enhancement", Proceedings of SPIE, Vol. 7708, pp. 770--811, 2010.

[29]

M. C Hanumantharaju, M. Ravishankar, D. R Rameshbabu and V. N Manjunath Aradhya, "An Efficient Metric for Evaluating the Quality of the Color Image Enhancement", Proceedings of Indian International Conference on Artificial Intelligence, Tumkur, India, 2011, pp. 1016--1026.

Cited By

Vidyasagar KKumar A(2024)Optimizing Preprocessing Techniques for Improved Analysis of Lung Cancer in MRI Images *2024 Fourth International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)10.1109/MPCIT62449.2024.10892653(59-64)Online publication date: 13-Dec-2024
https://doi.org/10.1109/MPCIT62449.2024.10892653
Sudir PHanumantharaju MManjunath Aradhya V(2021)Efficient COVID-19 Diagnosis Approach Using Multi-scale Retinex and Convolution Neural NetworkData Engineering and Intelligent Computing10.1007/978-981-16-0171-2_49(523-530)Online publication date: 5-May-2021
https://doi.org/10.1007/978-981-16-0171-2_49
Hanumantharaju MManjunath Aradhya VHemantha Kumar G(2020)Understanding and Analysis of Enhanced COVID-19 Chest X-Ray ImagesIntelligent Systems and Methods to Combat Covid-1910.1007/978-981-15-6572-4_6(47-55)Online publication date: 27-Aug-2020
https://doi.org/10.1007/978-981-15-6572-4_6
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Index Terms

A particle swarm optimization method for tuning the parameters of multiscale retinex based color image enhancement
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation

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ICACCI '12: Proceedings of the International Conference on Advances in Computing, Communications and Informatics

August 2012

1307 pages

ISBN:9781450311960

DOI:10.1145/2345396

Editors:
Sabu M. Thampi,
El-Sayed El-Afry,
Javier Aguiar,
General Chairs:
K. Gopalan
Purdue University Calumet
,
Sabu M. Thampi
Indian Institute of Information Technology and Management - Kerala, India

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 03 August 2012

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ICACCI '12: 2012 International Conference on Advances in Computing, Communications and Informatics

August 3 - 5, 2012

Chennai, India

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Cited By

Vidyasagar KKumar A(2024)Optimizing Preprocessing Techniques for Improved Analysis of Lung Cancer in MRI Images *2024 Fourth International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)10.1109/MPCIT62449.2024.10892653(59-64)Online publication date: 13-Dec-2024
https://doi.org/10.1109/MPCIT62449.2024.10892653
Sudir PHanumantharaju MManjunath Aradhya V(2021)Efficient COVID-19 Diagnosis Approach Using Multi-scale Retinex and Convolution Neural NetworkData Engineering and Intelligent Computing10.1007/978-981-16-0171-2_49(523-530)Online publication date: 5-May-2021
https://doi.org/10.1007/978-981-16-0171-2_49
Hanumantharaju MManjunath Aradhya VHemantha Kumar G(2020)Understanding and Analysis of Enhanced COVID-19 Chest X-Ray ImagesIntelligent Systems and Methods to Combat Covid-1910.1007/978-981-15-6572-4_6(47-55)Online publication date: 27-Aug-2020
https://doi.org/10.1007/978-981-15-6572-4_6
Fergani BLaoubi KKholladi M(2018)A discrete particle swarm algorithm for geometric image inpaintingInternational Journal of Intelligent Engineering Informatics10.1504/IJIEI.2014.0662162:2/3(215-241)Online publication date: 13-Dec-2018
https://dl.acm.org/doi/10.1504/IJIEI.2014.066216
Kaur GBhardwaj NSingh P(2017)An Analytic Review on Image Enhancement Techniques Based on Soft Computing ApproachSensors and Image Processing10.1007/978-981-10-6614-6_26(255-265)Online publication date: 4-Oct-2017
https://doi.org/10.1007/978-981-10-6614-6_26
Wang YWang HYin CDai M(2016)Biologically inspired image enhancement based on RetinexNeurocomputing10.1016/j.neucom.2015.10.124177:C(373-384)Online publication date: 12-Feb-2016
https://dl.acm.org/doi/10.1016/j.neucom.2015.10.124
Pratama SPratiwi LAbraham AMuda A(2014)Computational Intelligence in Digital ForensicsComputational Intelligence in Digital Forensics: Forensic Investigation and Applications10.1007/978-3-319-05885-6_1(1-16)Online publication date: 2014
https://doi.org/10.1007/978-3-319-05885-6_1
Setty SSrinath NHanumantharaju M(2013)Development of multiscale retinex algorithm for medical image enhancement based on multi-rate sampling2013 International Conference on Signal Processing , Image Processing & Pattern Recognition10.1109/ICSIPR.2013.6497976(145-150)Online publication date: Feb-2013
https://doi.org/10.1109/ICSIPR.2013.6497976

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