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


  • 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



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.



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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.



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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.