Image Enhancement based on the Histogram Equalization and Multiresolution Discrete Stationary Wavelet Transform

Authors

  • Firas Mahmood Mustafa Chemical Engineering Dept., Technical College of Engineering, Duhok Polytechnic University And Department of Communications and Computer, College of Engineering, Nawroz University Duhok, Kurdistan Region – F.R. Iraq

DOI:

https://doi.org/10.25007/ajnu.v11n2a1323

Abstract

In recent years, due to the tremendous development that took place on the Internet and its applications in the aspects of human life, the demands of using digital images have also increased dramatically, and that opens up horizons for scientific research in the field of improving the quality of the digital images by removing the noise that caused by to processes that are applied within network transmissions like performing storage, retrieval, and encryption to preserve privacy. All these effects are yielded to reduce image quality and loss of visual information. To surmount this problem, image enhancement methods are used to eliminate the noise while preserving supreme exact details and essential characteristics as much as possible in the digital image. The wavelet image enhancement technique played a critical role in this field by attempts to reduce noise in the image while retaining the vital features of the image due to the capability to separate the image into sub-bands (sub-images) and influence the frequencies of each sub-band separately, where acquiring the original image content is essential to obtaining reliable performance.

Different enhancement techniques have been realized by many researchers so far. Each technique has its own privileges and shortcomings. In this work, a proposed procedure is presented and effectuated to the image modified by Additive White Gaussian Noise (AWGN). The proposed enhancement operation was achieved using the combination of Histogram Equalization with a two-dimensional stationary discrete wavelet transform (2D-SWT) as a multi-resolution analysis technique in image processing at three levels of decomposition to obtain revised results of the method of noise removing. To distinguish and eliminate noise from affected pixel points in the wavelet domain the 2D-SWT is used based on the hard and soft threshold systems on both high and low frequencies to decrease noise from the noisy image. Then, the multi-level 2D inverse wavelet transform (2D-IWT) is applied to eliminate noise and complete the synthesis of the image by the proposed image enhancement techniques.

In the end, the performance of the proposed methods has been evaluated by using the Peak Signal to Noise Ratio (PSNR). Experimental measurements determine that the results of the proposed techniques enhanced the PSNR by about (16.16%) with respect to the results of the related works, and the structure of the image quality has also been improved in terms of edges retaining and greater noise elimination.

 

Downloads

Download data is not yet available.

Author Biography

Firas Mahmood Mustafa, Chemical Engineering Dept., Technical College of Engineering, Duhok Polytechnic University And Department of Communications and Computer, College of Engineering, Nawroz University Duhok, Kurdistan Region – F.R. Iraq

Experienced Teaching Staff with a demonstrated history of working in the education management industry. Skilled in E-Learning, Analytical Skills, Coaching, Data Analysis, and Public Speaking. Strong education professional with a High school focused on High School/Secondary Diplomas and Certificates from ALSHARQIEA.
I received my BSc, MSc and PhD degrees from the University of Mosul-Iraq, College of Engineering, Electric engineering dept. at 1997, 2000 and 2007 respectively. I have a PhD in Computer Engineering, and I am a lecturer since 2007. Experience with IT projects, image Denoising systems, development and computer networks. I have served in Computer Engineering and Computer Science departments in various universities including ALHADBA, Mosul, Zakho, Nawroz, and Duhok Polytechnic University (DPU), since 1999. I have published a journal and conference papers in the fields of computer networking, optimization, Image processing, wavelet transform, and person recognition systems. I have given a series of courses on different topics within the computer engineering specialization for master students and also supervised a number of master's thesis, since 2009. Also, I was a member of OPATEL team for Erasmus + project with the European Union at DPU Duhok. From 2017 till now I returned to work at Nawroz University as a chairman of the CCE Dept.

https://orcid.org/0000-0002-8757-5303

 

References

Kumar, S., Kumar, P., Gupta, M. & Nagawat, A. K. (2010). Performance comparison of median and wiener filter in image de-noising. International Journal of Computer Applications, Number 4 - Article 7, 27–31. doi: 10.5120/1664-2241

Rai, R.K., Asnani, J., Sontakke, T.R. (2012). Review of shrinkage techniques for image denoising. International Journal of Computer Applications, Volume 42 - Number 19, 13–16. doi: 10.5120/5800-8009

Al-Azzawi A.G. (2012). Image denoising based using hybrid techniques mixed between (hard and soft threshold) with multiwavelet transform and multi-stage vector quantization. Diyala Journal for Pure Sciences. ISSN: 2222-8373. Vol:8, No. 3, 45–67.

Rajput S., and S. R. Suralkahalikar, (2013). Comparative Study of Image Enhancement Techniques. International Journal of Computer Science and Mobile Computing. ISSN 2320–088X, IJCSMC, 2(1),11–21.

Saxena C., and Deepak K., (2014). Noises and Image Denoising Techniques: A Brief Survey. International Journal of Emerging Technology and Advanced Engineering. (ISSN 2250-2459), 4(3),878-885.

Saha, M., Naskar, M. K. & Chatterji, B. N. (2015). Soft, Hard and Block Thresholding Techniques for Denoising of Mammogram Images. IETE Journal of Research, 61:2, 186-191, doi: 10.1080/03772063.2015.1009394

Saluja, R. and Boyat, A. (2015). Wavelet based image denoising using weighted high pass filtering coefficients and adaptive wiener filter. 2015 International Conference on Computer, Communication and Control (IC4). pp. 1-6, doi: 10.1109/IC4.2015.7375588.

Tai-sheng Z., (2015). Research on Image Denoising with Wavelet Transform and Finite Element Method. International Journal of Signal Processing, Image Processing and Pattern Recognition. 8(10), 363-374.

Shukla, H. S., and Verma, R. (2016). Hybrid bilateral filtering techniques for salt and pepper noise. International Journal of Advanced Research in Computer Science and Software Eng., 6,3, 11-15.

Sami, H. I., Firas M. M., and İbrahim T. O., (2016). A New Approach of Image Denoising Based on Discrete Wavelet Transform. Computer Applications & Research (WSCAR), 2016 World Symposium, IEEE Conference: Cairo, Egypt, doi: 10.1109/WSCAR.2016.30

Nithyananda C. R., Ramachandra A. C., and Preethi. (2016). Review on Histogram Equalization based Image Enhancement Technique. International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). ISBN: 978-1-4673-9940-1, doi: 10.1109/ICEEOT.2016.7755145.

Wang, J., Wu, J., Wu, Z., Jeong, J., & Jeon, G. (2017). Wiener filter-based wavelet domain denoising. Displays. 46, 37–41. doi: 10.1016/j.displa.2016.12.003.

Ramadhan A., Firas M., and Atilla E., (2017). Image Denoising by Median Filter in Wavelet Domain. The International Journal of Multimedia & Its Applications (IJMA). doi: 10.5121/ijma.2017.9104. 9(1), 31-40

Tayade P. M., and Bhosale, S.P. (2018). Medical Image Denoising and Enhancement using DTCWT and Wiener filter. International Journal of Advance Research, Ideas and Innovations in Technology (IJARIIT), 2018. 4(4).

Arora S., Megha A., Veepin K., and Divya G. (2018). Comparative study of image enhancement techniques using histogram equalization on degraded images. International Journal of Engineering & Technology, 7 (2.8) 468-471.

Koranga P., G. Singh, D. Verma, S. Chaube, A. Kumar, S. Pant. (2018). Image denoising based on wavelet transform using Visu thresholding technique. Int. J. Math. Eng. Manag. Sci. 3 444–449.

Xie, Y., Lichuan, N., Wang, M., & Chengcheng Li. (2019). Image Enhancement Based on Histogram Equalization. Journal of Physics Conference Series 1314(1):012161. doi: 10.1088/1742-6596/1314/1/012161

Mittal N., Ananya R. & Harshita G. (2019). Enhancement and Removal of Noise from Medical Images by Wavelet Transform Method. Proceedings of the Third International Conference on Electronics Communication and Aerospace Technology [ICECA 2019]. IEEE Conference Record # 45616; IEEE Xplore ISBN: 978-1-7281-0167-5

Ferzo, B.M., & Mustafa, F.M. (2020). Image Denoising in Wavelet Domain Based on Thresholding with Applying Wiener Filter. In 2020 International Conference on Computer Science and Software Engineering (CSASE), pp. 106-111. https://doi.org/10.1109/CSASE48920.2020.9142091

Mustafa F., Abdullah H., & Elci A. (2021). Image enhancement in wavelet domain based on histogram equalization and median filter. Journal of Engineering Research (JER), online edition. doi: https://doi.org/10.36909/jer.10697

Ye H., Keqin Su, and Shiming Huang. (2021). Image Enhancement Method Based on Bilinear Interpolating and Wavelet Transform. 2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). pp. 1147-1150, doi: 10.1109/IAEAC50856.2021.9390624.

Jeevan K M, Anne Gowda A B, Padmaja V K. (2021). An image enhancement method based on Gabor filtering in wavelet domain and adaptive histogram equalization. Indonesian Journal of Electrical Engineering and Computer Science, Vol. 21, No. 1, pp. 146~153. doi: 10.1109/IAEAC50856.2021.9390624

Downloads

Published

2022-04-23

How to Cite

Mustafa, F. M. (2022). Image Enhancement based on the Histogram Equalization and Multiresolution Discrete Stationary Wavelet Transform. Academic Journal of Nawroz University, 11(2), 50–59. https://doi.org/10.25007/ajnu.v11n2a1323

Issue

Vol. 11 No. 2 (2022)

Section

Articles

License

Copyright (c) 2022 Firas Mahmood Mustafa

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Authors retain copyright

The use of a Creative Commons License enables authors/editors to retain copyright to their work. Publications can be reused and redistributed as long as the original author is correctly attributed.

 

  1. Copyright

 

  1. The researcher(s), whether a single or joint research paper, must sell and transfer to the publisher (the Academic Journal of Nawroz University) through all the duration of the publication which starts from the date of entering this Agreement into force, the exclusive rights of the research paper/article. These rights include the translation, reuse of papers/articles, transmit or distribute, or use the material or parts(s) contained therein to be published in scientific, academic, technical, professional journals or any other periodicals including any other works derived from them, all over the world, in English and Arabic, whether in print or in electronic edition of such journals and periodicals in all types of media or formats now or that may exist in the future. Rights also include giving license (or granting permission) to a third party to use the materials and any other works derived from them and publish them in such journals and periodicals all over the world. Transfer right under this Agreement includes the right to modify such materials to be used with computer systems and software, or to reproduce or publish it in e-formats and also to incorporate them into retrieval systems.

 

  1. Reproduction, reference, transmission, distribution or any other use of the content, or any parts of the subjects included in that content in any manner permitted by this Agreement, must be accompanied by mentioning the source which is (the Academic Journal of Nawroz University) and the publisher in addition to the title of the article, the name of the author (or co-authors), journal’s name, volume or issue, publisher's copyright, and publication year.

 

  1. The Academic Journal of Nawroz University reserves all rights to publish research papers/articles issued under a “Creative Commons License (CC BY-NC-ND 4.0) which permits unrestricted use, distribution, and reproduction of the paper/article by any means, provided that the original work is correctly cited.

 

  1. Reservation of Rights

The researcher(s) preserves all intellectual property rights (except for the one transferred to the publisher under this Agreement).

  1. Researcher’s guarantee

The researcher(s) hereby guarantees that the content of the paper/article is original. It has been submitted only to the Academic Journal of Nawroz University and has not been previously published by any other party.

In the event that the paper/article is written jointly with other researchers, the researcher guarantees that he/she has informed the other co-authors about the terms of this agreement, as well as obtaining their signature or written permission to sign on their behalf.

The author further guarantees:

  • The research paper/article does not contain any defamatory statements or illegal comments.
  • The research paper/article does not violate other's rights (including but not limited to copyright, patent, and trademark rights).

This research paper/article does not contain any facts or instructions that could cause damages or harm to others, and publishing it does not lead to disclosure of any confidential information.