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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PROtek : Jurnal Ilmiah Teknik Elektro
Mohd Shafry Mohd Rahim
Universiti Teknologi Malaysia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

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Enhancement of Unevenly Illuminated Images:an Experiment Based Review Younis, Zainab; Mohd Rahim, Mohd Shafry; Mohamed, Farhan Bin
PROtek : Jurnal Ilmiah Teknik Elektro Vol 12, No 2 (2025): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v12i2.8533

Abstract

Low-lighting conditions pose significant challenges to captured images and result in degraded image quality, characterized by poor visibility, imbalanced illumination, increased noise, limited contrast, inaccurate colours, and loss of detail. In recent years, the development of effective low-light enhancement techniques has attracted considerable attention from researchers and practitioners in various fields, such as surveillance, photography, forensics, and medical imaging. This article comprehensively overviews advances in low-light image enhancement methods, techniques, and algorithms. This review summarizes the working mechanism for each reviewed algorithm, implements it, provides the results, and analyses them, highlighting the concept, advantages, and disadvantages. Overall, this review offers a comprehensive resource for researchers and practitioners interested in knowing the latest technologies and methods for low-light image enhancement. It provides insights into current challenges, promising solutions, and future directions for advancing the field of low-light imaging. Finally, it benefits various researchers by describing the available concepts, what pros to consider, and what cons to avoid when developing their algorithms.
Color Image Denoising Methods: A Laconic Review Younis, Zainab; Mohd Rahim, Mohd Shafry; Mohamed , Farhan Bin
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 11 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v11i3.31200

Abstract

Color image denoising is an essential process in image processing, intending to remove noise from images while preserving the important image details, for instance, edges, resolution, and accuracy. This paper presents an experiment-based review of the recent methods of color image denoising algorithms, focusing on their strengths, limitations, complexity, findings, accuracy, and comparative performance. Therefore, eight methods in color image denoising with different concepts were reviewed and evaluated under a reliable experimental environment. The evaluation was conducted using a dataset collected from three different sources, such as a professional DSLR camera, various mobile devices, and the MIT-Adobe database, tested under different real-world noise conditions. The reviewed methods are assessed by three preceding metrics were selected as no-reference metrics to evaluate real color images where clean reference images are unavailable: fast image sharpness estimation (FISH), no-reference structure similarity (NRSS), sparsity, and dominant-orientation quality index (SDQI), objectively, along with subjective visual analysis. The results demonstrate that the Total Variation with Split Bregman (TVSB) algorithm achieved the highest performance and exceeded the other methods. Reviewed methods showed competitive results in fine structure, details, and preserving edges.  Additionally, the study discusses future recommendations for improving the effectiveness of these algorithms. Finally, this research is carried out systematically and empirically and focuses on the merits and demerits of their performance. It provides stepwise guidance on how to systematically target a particular approach in the color image denoising process, which highlights the practical and theoretical disparity. Moreover, it serves as a rich and source for scholars intending to develop algorithms in this domain.  
Co-Authors Mohamed , Farhan Bin Mohamed, Farhan Bin Younis, Zainab